{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "960ceacb-3c3f-484c-95b9-172bd009b1a4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is a generic code for drawing a state's Home Districts for neutral map estimation\n",
      "In this code, we use the term 'tract' generically to refer the base building block, usually vtd's\n"
     ]
    }
   ],
   "source": [
    "#  THIS IS THE PRIMARY VERSION TO USE FOR ALL STATES  #from MO 5/26/24\n",
    "print(\"This is a generic code for drawing a state's Home Districts for neutral map estimation\") #Jan'24\n",
    "print(\"In this code, we use the term 'tract' generically to refer the base building block, usually vtd's\")\n",
    "import shapely\n",
    "from shapely.geometry import Point, LineString, Polygon\n",
    "from shapely.ops import nearest_points, transform\n",
    "from shapely.affinity import translate, scale\n",
    "import geopandas as gpd\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from numpy import random\n",
    "from scipy.stats import norm\n",
    "from scipy.optimize import minimize, minimize_scalar\n",
    "import math\n",
    "import time\n",
    "import ast\n",
    "# from HDmethods import *   #I want to implement this, but my HDmethods require shapely functions\n",
    "# see https://stackoverflow.com/questions/66877728/proper-way-to-use-import-when-calling-external-function for a future workaround\n",
    "\n",
    "dummyPoly = Polygon([(0,0),(0,1),(1,1)])\n",
    "#handy function for plotting Polygon or multiPolygon tracts and precincts\n",
    "def plotPoly(inputPoly,LW=1):\n",
    "    dummyPoly = Polygon([(0,0),(0,1),(1,1)])\n",
    "    if inputPoly.geom_type == dummyPoly.geom_type:\n",
    "        x,y = inputPoly.exterior.xy\n",
    "        plt.plot(x,y,lw=LW)\n",
    "    else:\n",
    "        for geom in inputPoly.geoms:\n",
    "            if geom.area > 0:  #to avoid error with LineString geom parts\n",
    "                x,y = geom.exterior.xy\n",
    "                plt.plot(x,y,lw=LW)  \n",
    "def plotCenter(t,geom,FONTSIZE=10):\n",
    "    plt.text(geom.centroid.x,geom.centroid.y,t,ha='center',fontsize=FONTSIZE)\n",
    "    \n",
    "def r3(number):\n",
    "    result = round(number,3)\n",
    "    return result\n",
    "\n",
    "def r5(number):\n",
    "    result = round(number,5)\n",
    "    return result\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2ab4a3d5-f4e7-4aec-b81c-0e786cd35b57",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def getWeightedAvgAndSD(LIST, WEIGHTS):  #from IN\n",
    "    nWeights = len(WEIGHTS)\n",
    "    normWeights = [WEIGHTS[i] / np.sum(WEIGHTS) for i in range(nWeights) ]\n",
    "    AVG = 0.\n",
    "    for i, value in enumerate(LIST):\n",
    "        AVG += normWeights[i] * value\n",
    "    sumVar = 0.\n",
    "    for i, value in enumerate(LIST):\n",
    "        sumVar += normWeights[i] * (value - AVG)**2\n",
    "    SD = sumVar ** 0.5     #don't need to normalize again since weights were normalized\n",
    "    return AVG, SD\n",
    "\n",
    "def squish(shapeList, cutLINE, farLINE, newFarLINE):\n",
    "    \"\"\"\n",
    "    This method compresses a list of shapes lying between the cutLINE and the farLINE)\n",
    "    such that the Polygons now lie between the cutLINE and the newFarLINE, which is closer to the cutLINE\n",
    "    Used to compress state outcroppings into a more compact state representation.\n",
    "     (I tried doing this point by point (see #'s), but this overdistorted geometries.)\n",
    "      (#This was a manual alternative to shapely.affinity.scale and .translate operations)\n",
    "       So instead, we run this AFTER established untransformed map topology, and \n",
    "        we simply scale and translate each unit.  This loses true connectivity.\n",
    "        Scaling is all lengths scale by compression of distance\n",
    "    The cut, far, and newFar LineString segments are preferably parallel\n",
    "    The method returns the modified shapes of all pollys\n",
    "    \"\"\"\n",
    "    if cutLINE.intersects(farLINE) or cutLINE.intersects(newFarLINE):\n",
    "        print(\"cutLine,farLine, newFarLine were\",cutLINE, farLINE, newFarLINE)\n",
    "        raise Exception(\"ERROR: the proposed cutLine intersects the current or proposed far line\")\n",
    "    newPollys = list()\n",
    "    for polly in shapeList:\n",
    "        pollyCP = polly.centroid\n",
    "        cutPt =     nearest_points(cutLINE,   pollyCP)[0]\n",
    "        farPt =     nearest_points(farLINE,   pollyCP)[0]\n",
    "        newFarPt =  nearest_points(newFarLINE,pollyCP)[0]\n",
    "        curr_cutX, curr_cutY =            pollyCP.x - cutPt.x, pollyCP.y -  cutPt.y\n",
    "        currFar_CutX , currFar_CutY  =    farPt.x - cutPt.x, farPt.y   -  cutPt.y\n",
    "        new_currFarX, new_currFarY =      newFarPt.x - farPt.x, newFarPt.y - farPt.y\n",
    "        newFar_CutX,  newFar_CutY =       newFarPt.x - cutPt.x, newFarPt.y   -  cutPt.y\n",
    "        distanceRatio = newFarPt.distance(cutPt)/farPt.distance(cutPt) #scale area ^length^2\n",
    "        XOFF,YOFF = 0., 0.\n",
    "        XFACT, YFACT = 1., 1.  #default = no stretch\n",
    "        # basic equation: (new-cut)/(curr-cut) = (newFar-cut)/(currFar - cut)\n",
    "        #  or: (new-curr)  = (curr-cut)*(newFar-currFar)/(currFar - cut)   # -1 to both sides\n",
    "        if currFar_CutX != 0:\n",
    "            XOFF =  curr_cutX * new_currFarX / currFar_CutX\n",
    "            XFACT =              newFar_CutX / currFar_CutX\n",
    "        if currFar_CutY != 0:\n",
    "            YOFF =  curr_cutY * new_currFarY / currFar_CutY\n",
    "            YFACT =              newFar_CutY / currFar_CutY\n",
    "        newPolly = translate(polly,xoff=XOFF,yoff=YOFF)\n",
    "        newPolly = scale(newPolly, xfact=XFACT, yfact=YFACT, origin='centroid')\n",
    "        newPollys.append( newPolly )       \n",
    "    return newPollys\n",
    "\n",
    "def getHDcp(TRACTCP,TRACTPOP, TRACTLIST, SPLITTRACTNO = -777,SPLITTRACTUSE = 1.):  #population centerpoint of a Home District or county (cluster)\n",
    "    cpx, cpy, sumPop = 0.,0., 0.\n",
    "    for tt in TRACTLIST:\n",
    "        USE = 1.\n",
    "        if tt ==    SPLITTRACTNO:\n",
    "            USE =   SPLITTRACTUSE\n",
    "        sumPop += USE*TRACTPOP[tt]\n",
    "        cpx +=    USE*TRACTPOP[tt] * TRACTCP[tt].x\n",
    "        cpy +=    USE*TRACTPOP[tt] * TRACTCP[tt].y\n",
    "    HDCP_ = Point(cpx/sumPop, cpy/sumPop)\n",
    "    return HDCP_\n",
    "\n",
    "#  The below four methods are TO SNAP to HD SHAPES without any solving / iteration\n",
    "def buildWedge(CP,STARTANGLE, ENDANGLE, RR,XSCALE=1.0):\n",
    "    \"\"\"\n",
    "    This method creates triangular wedges from a centerpoint, wedge start and end angles, and wedge radius.\n",
    "    The optional xScale parameter is the ratio of longitude to latitude lengths scales (<<1 for far from equator)\n",
    "    It passes back a SINGLE wedge polygon\n",
    "    \"\"\"\n",
    "    A0 = STARTANGLE\n",
    "    A1 = ENDANGLE\n",
    "    PT1 = Point(CP.x + RR/XSCALE*math.cos(A0),  CP.y + RR*math.sin(A0) )\n",
    "    PT2 = Point(CP.x + RR/XSCALE*math.cos(A1),  CP.y + RR*math.sin(A1) )\n",
    "    WEDGEPOLY = Polygon( [CP,PT1, PT2 ])\n",
    "    return WEDGEPOLY\n",
    "\n",
    "def buildPoly(CP, RADII, ANGLES, XSCALE = 1.0):  #reconstructs a 4-tri polygon from four HD wedges emanating from the centerpoint\n",
    "    Pt = [Point(0,0)]*12                      #xScale has same meaning as in buildWedge\n",
    "    for nW in range(4): \n",
    "        ccwAngle = ANGLES[nW]  #these two are the angles at start and end of nth wedge\n",
    "        cwAngle =  ANGLES[ int((nW+1)%4) ]  \n",
    "        Pt[nW*2] =   Point(CP.x + RADII[nW]/XSCALE*math.cos(ccwAngle), CP.y + RADII[nW]*math.sin(ccwAngle) )\n",
    "        Pt[nW*2+1] = Point(CP.x + RADII[nW]/XSCALE*math.cos( cwAngle), CP.y + RADII[nW]*math.sin( cwAngle) )        \n",
    "    POLLY = Polygon([Pt[0],Pt[1],Pt[2],Pt[3],Pt[4],Pt[5],Pt[6],Pt[7] ])\n",
    "    return POLLY\n",
    "\n",
    "def buildArcPoly(CP, RADII, ANGLES, XSCALE = 1.0):  #reconstructs a fuller polygon from four HD wedges emanating from the centerpoint\n",
    "    twoPi = 2. * 3.1415926   #xScale has same meaning as in buildWedge\n",
    "    POINTS = list()                   \n",
    "    for nW in range(4): \n",
    "        ccwAngle = ANGLES[nW] % twoPi                 #these two are the angles at start and end of nth wedge\n",
    "        cwAngle =  ANGLES[ int((nW+1)%4) ] % twoPi \n",
    "        midAngle = [0.75*ccwAngle + 0.25*cwAngle , 0.25*ccwAngle + 0.75*cwAngle ]  #avoid s sampling cone center for wide angles\n",
    "        if abs (ccwAngle - cwAngle) > 3.1415926 :  #angles straddle angle=0\n",
    "            midAngle = [0.75*(ccwAngle - twoPi) + 0.25*cwAngle , 0.25*(ccwAngle -twoPi) + 0.75*cwAngle ]\n",
    "        angList = [ccwAngle] + midAngle + [cwAngle]\n",
    "        for ang in angList:\n",
    "            POINTS.append(Point(CP.x + RADII[nW]/XSCALE*math.cos(ang), CP.y + RADII[nW]*math.sin(ang) ) )\n",
    "                          \n",
    "    POLLY = Polygon(POINTS)\n",
    "    return POLLY\n",
    "\n",
    "def getPolyPop(POLLY, TRACTCP, TRACTPOP, CANDIDATELIST ):  #simple capture of pop points contained by a polygon\n",
    "    WPOP, WLIST = 0., list()\n",
    "    for tt in CANDIDATELIST:\n",
    "        if POLLY.contains(TRACTCP[tt]):\n",
    "            WPOP += TRACTPOP[tt]\n",
    "            WLIST.append(tt)\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def getNonCPP(POLLY, HC, TRACTCP, TRACTPOP, COUNTYGEOM, COUNTYPOP, COUNTYTRACTLIST, NEIGHBORCOUNTYLIST) : #nonCounty wedgePop\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by a POLLY polygon for counties contiguous with the Home County (no hop-overs)\n",
    "    , EXCLUDING the home county for the centerpoint of the wedge.  This should be more efficient than probing every unit in the map\n",
    "    After each county is checked, it goes into the checked list so we don't re-check, then we recursively probe county neighbors\n",
    "    \"\"\"\n",
    "    WPOP, WLIST = 0., list()\n",
    "    checkedClist = [HC]   #dynamic list of counties we've already checked.  We probed the home county in getPolyPop\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "                        if POLLY.contains(COUNTYGEOM[cc]):\n",
    "                            WPOP += COUNTYPOP[cc]\n",
    "                            WLIST += COUNTYTRACTLIST[cc]\n",
    "                        else:\n",
    "                            for tt in COUNTYTRACTLIST[cc]:\n",
    "                                if POLLY.contains(TRACTCP[tt]):\n",
    "                                    WPOP += TRACTPOP[tt]\n",
    "                                    WLIST.append(tt)\n",
    "        #below is temp debug\n",
    "        #print(len(intersectedClist),WPOP, len(WLIST),\"counties probed, pop, len(tractList)\")\n",
    "        latestClist = newClist.copy()\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def getNonHCunits(POLLY, HC, UNITLIST, UNITCP, UNITPOP, ALLFUSEDCOUNTIES, AREAFRAC, COUNTYGEOM, \n",
    "                  NEIGHBORCOUNTYLIST, COUNTYUNITLIST):\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by a POLLY polygon for counties contiguous with the Home County (no hop-overs)\n",
    "    , EXCLUDING the home county.  This should be more efficient than probing every unit in the map\n",
    "    After each county is checked, it goes into the checked list so we don't re-check, then we recursively probe county neighbors\n",
    "    \"unit counties\" are added as whole units if a sufficient area fraction is captured.  For non-unitCs, we probe each component vtd / tract\n",
    "    \"\"\"\n",
    "    UPOP, ULIST = 0., list()\n",
    "    checkedClist = [HC]   #dynamic list of counties we've already checked.  We probed the home county before we called this method\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        #1/9/24 - DO WE NEED TO MODIFY THE ORDER BELOW TO AVOID CREATING HOLES AND ENCLAVES ??  #\n",
    "        \n",
    "        for c in latestClist:\n",
    "            for cc in list( set(NEIGHBORCOUNTYLIST[c]).difference(set(ALLFUSEDCOUNTIES)) ):\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        if cc+0.5 in UNITLIST:\n",
    "                            if POLLY.intersection(COUNTYGEOM[cc]).area >=  AREAFRAC[cc] * COUNTYGEOM[cc].area :\n",
    "                                intersectedClist.append(cc)   #for unit counties, intersections count only if they capture sufficient area\n",
    "                                newClist.append(cc)\n",
    "                                UPOP += UNITPOP[UNITLIST.index(cc+0.5)]\n",
    "                                ULIST.append( UNITLIST.index(cc+0.5) )\n",
    "                        else:                           \n",
    "                            intersectedClist.append(cc)\n",
    "                            newClist.append(cc)\n",
    "                            if POLLY.contains(COUNTYGEOM[cc]):\n",
    "                                unitsToAdd = COUNTYUNITLIST[cc]\n",
    "                                UPOP += np.sum(  [ UNITPOP[uu] for uu in unitsToAdd ]  )\n",
    "                                ULIST += unitsToAdd\n",
    "                            else:\n",
    "                                for uu in COUNTYUNITLIST[cc]:\n",
    "                                    if POLLY.contains(UNITCP[uu]):\n",
    "                                        UPOP += UNITPOP[uu]\n",
    "                                        ULIST.append(uu)\n",
    "        latestClist = newClist.copy()\n",
    "        \n",
    "    return UPOP, ULIST\n",
    "\n",
    "def clusterSwell(CP_, CCBgeom, CCBpop, allUnits, unitCP, unitPop, unitNbrs, borderUnits, TGTPOP):\n",
    "    \"\"\"\n",
    "    This method grows a Home District by \"swelling\" from a corner county cluster.  First, we add the full cluster,\n",
    "     then we add closest neighbor units to the home district centerpoint CP_ until we reach the TGTPOP\n",
    "     new for MN 4/7/24 - don't enforce contiguity here -- too slow -- fix in cleanup stage instead\n",
    "     \"\"\"\n",
    "    hd_CCBdist = [CP_.distance(geo) for geo in CCBgeom]\n",
    "    CCBno = hd_CCBdist.index(np.min(hd_CCBdist))  #ID's the closest cluster to this HD center.  Should contain the HD, but rarely will not\n",
    "    unitNo = allUnits.index(CCBno+0.25)\n",
    "    newList, prevList, addedList, addedPop = [unitNo], [unitNo], [unitNo], unitPop[unitNo]  #seed with the cluster pop and unit\n",
    "    while addedPop < 0.99 * TGTPOP and len(newList) > 0:\n",
    "        tryList = getAdjoiners(addedList,unitNbrs)\n",
    "        tryDist = [ CP_.distance(unitCP[UU]) for UU in tryList ]\n",
    "        idx = np.argsort(tryDist)\n",
    "        idxNo, newList = 0, list()\n",
    "        haveNotAdded = True\n",
    "        while idxNo < len(tryList) and haveNotAdded:\n",
    "            UU = tryList[idx[idxNo]]\n",
    "            if unitPop[UU] + addedPop < 1.01 * TGTPOP :  #and wontEnclave(UU, addedList, unitNbrs, borderUnits) :  #we'll post-fix contig'y\n",
    "                newList.append(UU)\n",
    "                addedList.append(UU)\n",
    "                addedPop += unitPop[UU]\n",
    "                haveNotAdded = False\n",
    "            idxNo +=1\n",
    "        prevList = newList.copy()\n",
    "        \n",
    "    return addedPop, addedList\n",
    "            \n",
    "def getFakeHC(HDPOLLY, HC, CCBlist, countyGeom, MAP) :\n",
    "    \"\"\"\n",
    "    This method is for setting a fake home county for counties in corner clusters, so that county neighbors can be found budding from the \"home county\"\n",
    "    We pick the county in the cluster closest to the map center and intersecting the HDpoly.  This will be an active county on the cluster boundary   \n",
    "    \"\"\"\n",
    "    MAPcenter = MAP.centroid\n",
    "    for L in CCBlist:\n",
    "        if HC in L:\n",
    "            distList, cList = list(), list()\n",
    "            for C in L:\n",
    "                if HDPOLLY.intersects(countyGeom[C]):\n",
    "                    distList.append(countyGeom[C].distance(MAPcenter))\n",
    "                    cList.append(C)\n",
    "    fakeHC = cList[distList.index(np.min(distList)) ]\n",
    "    return fakeHC\n",
    "\n",
    "def getLongDist(CP1, CP2, xScale = 1.0): #distance between two points with EW distance scaled down by latitude\n",
    "    #LAT = MAP.centroid.y\n",
    "    #xScale = (1. - 1.089* abs(LAT/90)**1.9)\n",
    "    dist = ( xScale*xScale * (CP1.x - CP2.x)*(CP1.x - CP2.x)  +  (CP1.y - CP2.y)*(CP1.y - CP2.y) ) **0.5 \n",
    "    return dist\n",
    "\n",
    "# THESE ARE THE METHODS USED IN SOLVING HD SHAPES\n",
    "def buildWedge(CP,STARTANGLE, ENDANGLE, RR,XSCALE=1.0):\n",
    "    \"\"\"\n",
    "    This method creates triangular wedges from a centerpoint, wedge start and end angles, and wedge radius.\n",
    "    It passes back a SINGLE wedge polygon\n",
    "    \"\"\"\n",
    "    A0 = STARTANGLE\n",
    "    A1 = ENDANGLE\n",
    "    PT1 = Point(CP.x + RR/XSCALE*math.cos(A0),  CP.y + RR*math.sin(A0) )\n",
    "    PT2 = Point(CP.x + RR/XSCALE*math.cos(A1),  CP.y + RR*math.sin(A1) )\n",
    "    WEDGEPOLY = Polygon( [CP,PT1, PT2 ])\n",
    "    return WEDGEPOLY\n",
    "\n",
    "def getCountyWP(T, WEDGEPOLY, TRACTCP, TRACTPOP, CANDIDATELIST ):  #simple capture of pop points in a wedge excluding a point\n",
    "        WPOP, WLIST = 0., list()\n",
    "        for tt in CANDIDATELIST:\n",
    "            if tt != T and WEDGEPOLY.contains(TRACTCP[tt]):\n",
    "                WPOP += TRACTPOP[tt]\n",
    "                WLIST.append(tt)\n",
    "        return WPOP, WLIST\n",
    "\n",
    "def getNonCWP(WEDGEPOLY, HC, TRACTCP, TRACTPOP, COUNTYGEOM, COUNTYPOP, COUNTYTRACTLIST, NEIGHBORCOUNTYLIST) : #nonCounty wedgePop\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by an infinite polygonal wedge for counties contiguous with the Home County (no hop-overs)\n",
    "    , EXCLUDING the home county for the centerpoint of the wedge.  This should be more efficient than going tract-by-tract\n",
    "    After each county is checked, it goes into the checked list so we don't re-check.  Next round = nonchecked neighbors of current round\n",
    "    \"\"\"\n",
    "    WPOP, WLIST = 0., list()\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if WEDGEPOLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "                        if WEDGEPOLY.contains(COUNTYGEOM[cc]):\n",
    "                            WPOP += COUNTYPOP[cc]\n",
    "                            WLIST += COUNTYTRACTLIST[cc]\n",
    "                        else:\n",
    "                            for tt in COUNTYTRACTLIST[cc]:\n",
    "                                if WEDGEPOLY.contains(TRACTCP[tt]):\n",
    "                                    WPOP += TRACTPOP[tt]\n",
    "                                    WLIST.append(tt)\n",
    "        #below is temp debug\n",
    "        #print(len(intersectedClist),WPOP, len(WLIST),\"counties probed, pop, len(tractList)\")\n",
    "        latestClist = newClist.copy()\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def isIncludedA(STARTa, ENDa, TESTa): #determines if a test angle is between a start and end angle (True)\n",
    "    \"\"\"\n",
    "    The start angle must be less than the end angle when placed on the [0, 2 pi] interval  (ccw convention)\n",
    "    \"\"\"\n",
    "    pi = 3.141592653\n",
    "    STARTa, ENDa, TESTa = STARTa % (2.*pi), ENDa % (2.*pi), TESTa % (2.*pi)  #place on the 2pi interval\n",
    "    isIncludedA = False\n",
    "    if STARTa  > ENDa :  #included angle straddles east\n",
    "        if   TESTa  >= STARTa or TESTa < ENDa :  #near-east between the two\n",
    "            isIncludedA = True\n",
    "    else:\n",
    "        if TESTa >= STARTa and TESTa < ENDa :  #normal case\n",
    "            isIncludedA = True\n",
    "    return isIncludedA\n",
    "\n",
    "def getNonCWP_c(STARTANGL, ENDANGL, HC, TRACTCP,TRACTPOP,COUNTYGEOM,COUNTYPOP,COUNTYTRACTLIST,\n",
    "                                    NEIGHBORCOUNTYLIST, UUDIST, UUANGLE, WEDGEPOLY) :\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by a polygonal wedge for counties contiguous with the Home County (no hop-overs),\n",
    "    EXCLUDING the home county for the centerpoint of the wedge.  This should be more efficient than going tract-by-tract\n",
    "    After each county is checked, it goes into the checked list so we don't re-check.  Next round = nonchecked neighbors of current round\n",
    "    Unlike its getNonCWP vanilla parent, this one uses angles rather than infinite wedges for units (still wedges for counties)\n",
    "    \"\"\"\n",
    "    WPOP, WLIST = 0., list()\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if WEDGEPOLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "                        if WEDGEPOLY.contains(COUNTYGEOM[cc]):\n",
    "                            WPOP += COUNTYPOP[cc]\n",
    "                            WLIST += COUNTYTRACTLIST[cc]\n",
    "                        else:\n",
    "                            for tt in COUNTYTRACTLIST[cc]:\n",
    "                                if isIncludedA(STARTANGL, ENDANGL, UUANGLE[tt]): #WEDGEPOLY.contains(TRACTCP[tt]):\n",
    "                                    WPOP += TRACTPOP[tt]\n",
    "                                    WLIST.append(tt)\n",
    "        #below is temp debug\n",
    "        #print(len(intersectedClist),WPOP, len(WLIST),\"counties probed, pop, len(tractList)\")\n",
    "        latestClist = newClist.copy()\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def getExitAngle(CP,WEDGEPOLY, MAP, A0, A1):\n",
    "    \"\"\"\n",
    "    This code determines the orientation angle from a CenterPoint to the intersection of a wedge with an exterior boundary\n",
    "    If an intersection is not found, we just take the average angle of the wedge start/stop angles A0, A1 as this orientation angle\n",
    "    MAP must be a single polygon for this to work in the revised code (tho could run thru all polygons in MAP if a multipolygon)\n",
    "    \"\"\"\n",
    "    EXITANGLE = 0.5* (A0 + A1) #this will be the angle from the x-axis to the exit beeline\n",
    "    if WEDGEPOLY.intersects(MAP.exterior):\n",
    "        edgeLine = WEDGEPOLY.intersection(MAP.exterior) #true state boundary line where wedge crossed it\n",
    "        closePoint = nearest_points(edgeLine,CP)[0]\n",
    "        dx = closePoint.x - CP.x       #this and below lines were indented in original code***\n",
    "        dy = closePoint.y - CP.y\n",
    "        EXITANGLE =  pi/2. * np.sign(dy)  #default in case dx=0\n",
    "        if (dx != 0. ):\n",
    "            EXITANGLE = math.atan(dy/dx) + random.uniform(-0.01,0.01) #add wiggle to avoid exact NESW orientation in gridded states\n",
    "            if dx < 0. :  #use complementary atan solution; boundary is west of tract centroid\n",
    "                EXITANGLE = pi + EXITANGLE\n",
    "    return EXITANGLE # this reorients 0th wedge to face boundary's closest point\n",
    "\n",
    "def getNewAngles(mWP, tWP, ADP, LEVEL_L, MINADJRATIO, MAXANGLE, MAXANGLERATIO, nUNFILLEDWEDGES): \n",
    "    \"\"\"\n",
    "    This method classifies Home Districts based on how their post-reoriented equi-angle max wedge pops stack up vs targets,\n",
    "     then changes wedge angles in some situations to pick up more population along the boundary\n",
    "    If there is one wedge that will fall short of a quarter district pop, then we adjust angles if it is sufficiently short    \n",
    "    (Using \"HD2\" code, the opposite wedge's pop will be constrained as well.)\n",
    "    If there are two opposite-facing constrained wedges, we do not adjust angles\n",
    "    If there are two adjacent constrained wedges, we classify as a corner (no angle change) if the adjacent wedge is sufficiently constrained,\n",
    "      otherwise we treat as a single constrained wedge\n",
    "    If there are three constrained wedges, the angles are unchanged; we use the 4th wedge to pick up all pop\n",
    "    If all four wedges are constrained, there is an error and we raise a flag.\n",
    "    mWP is the quadlist of maxWedgePops we would get by extending each wedge to the MAP boundary\n",
    "    tWP is the quadlist of targetWedgePops\n",
    "    LEVEL_L is the non-dimensional distance to the boundary at which we no longer adjust wedge angles to drive more near-boundary pop\n",
    "    MAXANGLERATIO is the max ratio of the wide angle (facing the boundary) to the normal angle (e.g. 90deg for four wedges) ...\n",
    "    but this is truncated near-boundary to MAXANGLE (e.g. 1.8 pi/2 instead of increasing all the way to 1.9 pi/2)\n",
    "      NOTE THAT this code does not consider nearly-shorted wedges -- those are a separate method called later if all mWP's > tWP's\n",
    "    \"\"\"   \n",
    "    isChange = False   #default; we are NOT changing angles\n",
    "    printDebuggg = False\n",
    "    NWEDGES = len(mWP)\n",
    "    avgWedgeAngle = 2.*math.pi / NWEDGES\n",
    "    minW = mWP.index(np.min(mWP))  #index of the wedge with the lowest max wedge pop\n",
    "    oppW = int( int(minW + NWEDGES/2) % NWEDGES )  #and its opposing wedge\n",
    "    Lstar = ( mWP[minW] / (0.25*ADP) )**0.5  #shortest wedge's nondim'l distance to boundary\n",
    "    \n",
    "    case = \"keep same wedge angles\" #default; no unfillable wedges or all but one are unfillable\n",
    "    if nUNFILLEDWEDGES >= NWEDGES:\n",
    "        raise Exception(\"ERROR! ALL WEDGES ARE CONSTRAINED for tract\",t,\".  IMPOSSIBLE!!\")\n",
    "    if nUNFILLEDWEDGES == 1:\n",
    "        case = \"constrain opp wedge\"\n",
    "        if Lstar >= levelL :\n",
    "            case = \"keep same wedge angles\"  #not close enough to boundary to distort HD shape\n",
    "    if nUNFILLEDWEDGES == 0 or nUNFILLEDWEDGES == NWEDGES - 1:  #far from boundary or with only one wedge w/large pop\n",
    "        case = \"keep same wedge angles\"   \n",
    "    if nUNFILLEDWEDGES == 2:  #must determine if opposite or adjacent           \n",
    "        if mWP[oppW] < tWP[oppW]:  #shorted wedges oppose each other, so ...\n",
    "            case = \"keep same wedge angles\" #...the HD shape will naturally widen to pick up adjacent pop\n",
    "        else:  #we have 2 adjacent (non-opposing) shorted wedges... but how shorted?  ID the adjacent wedge\n",
    "            for nW in range(NWEDGES):\n",
    "                if mWP[nW] < tWP[nW] and nW != minW :\n",
    "                    adjW = nW  #this is the adjacent wedge\n",
    "                    adjRatio = mWP[adjW] / tWP[adjW]\n",
    "            if adjRatio < minAdjRatio:  #we're close to a corner (this adjacentWedge is significantly constrained)\n",
    "                case = \"keep same wedge angles\"\n",
    "                if printDebuggg :\n",
    "                    print(\"Not adjusting wedge angles for tract\",t,\"as 2nd-sparsest wedge\",adjW,\"has pop\",mWP[adjW] )\n",
    "            else:\n",
    "                case = \"constrain opp wedge\"  #we will set the angles and target pops as if the adj wedge were not constrained\n",
    "    \n",
    "    if case == \"keep same wedge angles\":\n",
    "        isChange = False\n",
    "        WEDGEANGLE = [avgWedgeAngle for w in range(NWEDGES) ]\n",
    "\n",
    "    if case == \"constrain opp wedge\":  #Here, we modify wedge angles.  MWP's will be recalc'd outside the method\n",
    "        isChange = True  \n",
    "        wideAngle = min(MAXANGLE, avgWedgeAngle*max(  1,( 1.+(MAXANGLERATIO-1.)*(LEVEL_L - Lstar)/(LEVEL_L - 0.) )  ) )\n",
    "        WEDGEANGLE = [(2.*pi - 2. * wideAngle)/ (NWEDGES - 2.) for w in range(NWEDGES) ]  \n",
    "        WEDGEANGLE[minW] = wideAngle\n",
    "        WEDGEANGLE[oppW] = wideAngle\n",
    "    \n",
    "    return isChange, WEDGEANGLE\n",
    "\n",
    "def rebalanceTWPs(MWP, TWP, BARREDLIST=list()):\n",
    "    \"\"\"\n",
    "    This method iteratively increases targetWedgePops to accommodate wedges that have maxWedgePop < targetWedgePop.\n",
    "    The wedgePop gap is distributed equally among wedges that have some capacity and are not BARRED (e.g. an opposite wedge in HD2 method)\n",
    "     (If this pushes some wedges over capacity, this will be fixed in a later run through loop inside this method)\n",
    "    We also flag which wedges \"will fill\" = have sufficient capacity after the rebalancing of the targets to not use the entire maxWedgePoly\n",
    "    \"\"\"\n",
    "    DEBUGrTWP = False\n",
    "    NWEDGES = len(MWP)\n",
    "    unorderedCapacity = [MWP[w] - TWP[w] for w in range(NWEDGES) ]\n",
    "    idx = np.argsort(unorderedCapacity)\n",
    "    #for nn in range(NWEDGES):\n",
    "    #    print(MWP[idx[nn]])\n",
    "    if np.min(TWP) < 0.99 * np.average(TWP) and DEBUGrTWP:  #debug\n",
    "        for nn in range(NWEDGES):\n",
    "            print(\"barred list, orig MWP, TWP\",BARREDLIST, r3(MWP[nn]),r3(TWP[nn]) )\n",
    "    \n",
    "    for nn in range(NWEDGES):  #going from least to most maxWedgePop here ...\n",
    "        nW = idx[nn]\n",
    "        if MWP[nW] < TWP[nW]: #need to redistribute extra target to higher-capacity wedges ...\n",
    "            wedgePopGap = TWP[nW] - MWP[nW]\n",
    "            TWP[nW] = MWP[nW]  #max out this wedge\n",
    "            nReceivers = 0.\n",
    "            for WW in range(NWEDGES):\n",
    "                if MWP[WW] > TWP[WW] and WW not in BARREDLIST:  #this wedge could take at least a little more ....\n",
    "                    nReceivers += 1.\n",
    "            for WW in range(NWEDGES):\n",
    "                if MWP[WW] > TWP[WW] and WW not in BARREDLIST:  #this wedge could take at least a little more ....                    \n",
    "                    TWP[WW] += wedgePopGap / nReceivers  #... so give it equal share of the gap, even if this goes over; we'll correct in later loop\n",
    "                    \n",
    "    WILLFILL = [1]*NWEDGES\n",
    "    for nW in range(NWEDGES):\n",
    "        if MWP[nW] < 1.001* TWP[nW]:  #required pop nearly or truly requires the entire wedge\n",
    "            WILLFILL[nW] = 0 \n",
    "    if np.min(TWP) < 0.99 * np.average(TWP) and DEBUGrTWP:  #debug\n",
    "        print(\"adjusted TWP's are\",TWP)\n",
    "    return TWP, WILLFILL\n",
    "\n",
    "def solveWedge(nontractTWP,t, hC, STARTANGLE, ENDANGLE, MAXD, TOLERPOPS, tractCP, tractPop,\n",
    "               countyTractList, countyGeom, countyPop, neighborCountyLIST,XSCALE=1.0):\n",
    "    \"\"\"\n",
    "    #### NO LONGER USED; SEE FASTER SOLVEWEDGEB BASED ON UNIT-UNIT DISTANCES  *********\n",
    "    This heart of the code solves the wedge radius that gives the closest wedgePop to the TargetWedgePop (which excludes the home tractPop)\n",
    "    The wedge has a fixed starting and ending angle.  Its maximum diameter is angle-related to max diameter of the state map\n",
    "    It uses bisection, NOT scipy minimize to minimize the square error in the wedge pop vs. target\n",
    "    The method passes back the final wedge pop and list of tracts in the wedge\n",
    "    \"\"\"\n",
    "    chgLoopNo, maxLoopNo = 10., 22.  #when we will start relaxing the pop tolerance, and when we give up\n",
    "    includedAngl = ENDANGLE - STARTANGLE\n",
    "    guessedR = MAXD / math.cos(0.5*includedAngl)  #max possible wedge radius, accounting for possible wide angle\n",
    "    popTol = TOLERPOPS[0]  #default tolerance = e.g. within 0.7 an AVERAGE tract's population.\n",
    "    #                      We loosen toward half the MAX tractPop if not converging\n",
    "    \n",
    "    offsetPop = 88888888.  #to force a reduction the first time through the loop\n",
    "    dr = guessedR\n",
    "    loopNo = 0\n",
    "    while abs(offsetPop) > popTol and loopNo < maxLoopNo:\n",
    "        loopNo +=1\n",
    "        popTol = max(TOLERPOPS[0], TOLERPOPS[0] + (TOLERPOPS[1] - TOLERPOPS[0]) * (loopNo - chgLoopNo) / (maxLoopNo - chgLoopNo) )\n",
    "        dr = 0.5*dr\n",
    "        guessedR -= dr*np.sign(offsetPop)\n",
    "        \n",
    "        guessedPoly = buildWedge(tractCP[t],STARTANGLE, ENDANGLE, guessedR,XSCALE) \n",
    "        iCP, iClist =  getCountyWP(t,guessedPoly, tractCP, tractPop, countyTractList[hC])\n",
    "        nonCP, nonClist = getNonCWP(guessedPoly, hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyLIST)\n",
    "        offsetPop = iCP + nonCP - nontractTWP\n",
    "        #print(t,loopNo,r5(guessedR),int(iCP),int(nonCP),r3(offsetPop+nontractTWP),r3(nontractTWP),\"t,loop,R,iCP,nonCP,pop,target\")\n",
    "        if loopNo >= maxLoopNo-1:\n",
    "            print(\"WARNING. Looped\",loopNo,\"times for t,angles,R\",t,r3(STARTANGLE),r3(ENDANGLE),r5(guessedR),\n",
    "                  \"wedgePop offset, target are\",int(offsetPop), int(nontractTWP) )    \n",
    "    finalPop = iCP + nonCP\n",
    "    finalList = iClist + nonClist\n",
    "    return finalPop, finalList, guessedR, loopNo\n",
    "\n",
    "#above = bisection.  Below solveWedgeB uses static unit-unit distances\n",
    "# Also tried scipy minimize, which doesn't seem any faster\n",
    "\n",
    "def solveWedgeB(nontractTWP,T, HC, POLLY, TOLERPOP, TRACTCP, TRACTPOP, COUNTYNO,\n",
    "               COUNTYTRACTLIST, COUNTYGEOM, NEIGHBORCOUNTYLIST, UUDIST):\n",
    "    \"\"\"\n",
    "    This heart of the code solves the wedge radius that gives the closest wedgePop to the TargetWedgePop\n",
    "    We first determine which counties intersect the maxWedgePop to reduce the candidate list\n",
    "    We then go through the tract list from closest to farthest, adding any (from candidate counties) that intersect,\n",
    "     until the target pop is reached. Note that the passed UUDIST is the slice for unit t, not the full 2x2 array\n",
    "    \"\"\"\n",
    "    popTol = TOLERPOP  #default tolerance = e.g. within 0.7 an AVERAGE tract's population.\n",
    "    \n",
    "    #preliminary - restrict the found units to those in contiguous counties to the home county\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "        latestClist = newClist.copy()\n",
    "    \n",
    "    idx = np.argsort(UUDIST)  #sort order from closest to farthest to the home unit\n",
    "    \n",
    "    i, capturedPop, capturedList = 0, 0, list()\n",
    "    notFull = True\n",
    "    while notFull :  #capturedPop < nontractTWP - popTol : \n",
    "        i +=1    #this skips over the home tract\n",
    "        TT = idx[i]\n",
    "        if COUNTYNO[TT] in intersectedClist and TT != T:  #just to be sure\n",
    "            if POLLY.contains(TRACTCP[TT]):\n",
    "                capturedPop += TRACTPOP[TT]\n",
    "                capturedList.append(TT)\n",
    "                latestDist = UUDIST[TT]\n",
    "            if capturedPop > nontractTWP - popTol:\n",
    "                notFull = False\n",
    "                \n",
    "    return capturedPop, capturedList, latestDist    \n",
    "\n",
    "def solveWedgeC(nontractTWP,T, HC, POLLY, STARTANGL, ENDANGL, TOLERPOP, TRACTCP, TRACTPOP, COUNTYNO,\n",
    "               COUNTYTRACTLIST, COUNTYGEOM, NEIGHBORCOUNTYLIST, UUDIST, UUANGLE):\n",
    "    \"\"\"\n",
    "    This heart of the code solves the wedge radius that gives the closest wedgePop to the TargetWedgePop\n",
    "    We first determine which counties intersect the maxWedgePop to reduce the candidate list\n",
    "    We then go through the tract list from closest to farthest, adding any (from candidate counties) that\n",
    "    fall within the angle range (in lieu of wedgeB's check for intersection),\n",
    "     until the target pop is reached. Note that the passed UUDIST is the slice for unit t, not the full 2D array\n",
    "    \"\"\"\n",
    "    pi = 3.141592653\n",
    "    popTol = TOLERPOP  #default tolerance = e.g. within 0.7 an AVERAGE tract's population.\n",
    "    STARTANGL, ENDANGL = STARTANGL % (2.*pi), ENDANGL % (2.*pi)\n",
    "    #preliminary - restrict the found units to those in contiguous counties to the home county\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "        latestClist = newClist.copy()\n",
    "    \n",
    "    idx = np.argsort(UUDIST)  #sort order from closest to farthest to the home unit\n",
    "    \n",
    "    i, capturedPop, capturedList, latestDist = 0, 0, list(), 0.00001  #dummy value\n",
    "    notFull = True\n",
    "    while notFull and i < len(UUDIST) - 2 :  #capturedPop < nontractTWP - popTol : \n",
    "        i +=1    #this skips over the home tract\n",
    "        TT = idx[i]\n",
    "        if COUNTYNO[TT] in intersectedClist and TT != T:  #just to be sure\n",
    "            if isIncludedA(STARTANGL, ENDANGL, UUANGLE[TT]) : #POLLY.contains(TRACTCP[TT]):\n",
    "                capturedPop += TRACTPOP[TT]\n",
    "                capturedList.append(TT)\n",
    "                latestDist = UUDIST[TT]\n",
    "            if capturedPop > nontractTWP - popTol:\n",
    "                notFull = False\n",
    "                \n",
    "    return capturedPop, capturedList, latestDist \n",
    "\n",
    "\n",
    "def getPartialTract(t, HDTRACTLIST, offsetPop, UUDIST, tractPop, neighborLIST):\n",
    "    \"\"\"\n",
    "    If offsetPop is >0, this method identifies the tract with centroid farthest from Home t that can jettison at least offsetPop ...\n",
    "    ... by slicing out part of this tract.\n",
    "    If offsetPop <0, we ID a tract CLOSEST to Home t among neighbors of in-HD tracts to pick up a partial\n",
    "    We return the tractID and its new partial use\n",
    "    We have updated this method to pass the uuDist slice for tract t instead of computing tract distances inside here\n",
    "    \"\"\"\n",
    "    debugGPT = False\n",
    "    NTRACTS = len(tractCP)\n",
    "    bigDist = 9999999.\n",
    "    qualifyingTractList = list()\n",
    "    isWholeTract = False\n",
    "    if offsetPop > 0:\n",
    "        homeDist = [0.]*NTRACTS  #default = 0 to not get picked\n",
    "        for TT in HDTRACTLIST:\n",
    "            if tractPop[TT] > offsetPop:\n",
    "                qualifyingTractList.append(TT)\n",
    "        for TT in qualifyingTractList:\n",
    "            homeDist[TT] = UUDIST[TT]\n",
    "        if len(qualifyingTractList) == 0:  #very rare case where all in-HD tracts are too small.  Jettison nearly the whole farthest one\n",
    "            isWholeTract = True\n",
    "            for TT in HDTRACTLIST:\n",
    "                if tractPop[TT] > 0.9*np.average(tractPop): #set arbitrary min qualifying pop\n",
    "                    homeDist[TT] = UUDIST[TT]\n",
    "        targetT = homeDist.index(np.max(homeDist))\n",
    "        partialUseFrac = max(0.0001,(tractPop[targetT] - offsetPop)/tractPop[targetT] )\n",
    "        if debugGPT:\n",
    "            print(\"positive offsetPop =\",offsetPop,\", ID'd tract\",targetT,\"with pop\",tractPop[targetT] )\n",
    "    else: #pick up a partial\n",
    "        homeDist = [bigDist]*NTRACTS\n",
    "        for TT in HDTRACTLIST:\n",
    "            for TTT in neighborList[TT]:\n",
    "                if TTT not in qualifyingTractList and TTT not in HDTRACTLIST and tractPop[TTT] > abs(offsetPop):\n",
    "                    qualifyingTractList.append(TTT)\n",
    "        for TTT in qualifyingTractList:\n",
    "            homeDist[TTT] = UUDIST[TTT]\n",
    "        if len(qualifyingTractList) == 0 :  #rare case where most nearby tracts are small.  Add nearly the whole biggest one\n",
    "            isWholeTract = True\n",
    "            maxPop = 0.\n",
    "            targetT = -999\n",
    "            for TT in HDTRACTLIST:\n",
    "                for TTT in neighborList[TT]:\n",
    "                    if TTT not in qualifyingTractList and TTT not in HDTRACTLIST : # we'll take just one, even if doesn't fill gap\n",
    "                        qualifyingTractList.append(TTT)\n",
    "            for TTT in qualifyingTractList:\n",
    "                if tractPop[TTT] > maxPop:\n",
    "                    targetT = TTT\n",
    "                    maxPop = tractPop[targetT]\n",
    "        else:\n",
    "            targetT = homeDist.index(np.min(homeDist))\n",
    "        partialUseFrac = min(0.9999, -1.* offsetPop/tractPop[targetT] )\n",
    "        if debugGPT:\n",
    "            print(t,\"'s negative offsetPop =\",offsetPop,\", ID'd tract\",targetT,\"with pop\",tractPop[targetT] )\n",
    "    \n",
    "    return targetT, partialUseFrac\n",
    "\n",
    "def getAdjoiners(UNITLIST, UNITNBRS): #returns all units that neighbor a UNITLIST but are not in the UNITLIST \n",
    "    allNbrs = list()\n",
    "    for U in UNITLIST:\n",
    "        allNbrs = allNbrs + UNITNBRS[U]\n",
    "    adjoiners = list( set(allNbrs).difference(set(UNITLIST)) )\n",
    "    return adjoiners\n",
    "\n",
    "def get2nbrs(ULIST, UNITNBRS):\n",
    "    \"\"\"\n",
    "    Get the combined list of first- and second-level neighbors of a LIST, using neighborList connectivity.  Excludes the source list\n",
    "    \"\"\"\n",
    "    firstList =  getAdjoiners(ULIST, UNITNBRS)\n",
    "    secondList = getAdjoiners(firstList, UNITNBRS)\n",
    "    twoLevelList = list( set(firstList + secondList).difference(set(ULIST) ) )\n",
    "    return twoLevelList\n",
    "\n",
    "def getContigFromStarter(starter, VLIST, NEIGHBORLIST):  #all contiguous units in VLIST, starting from starter unit\n",
    "    foundList, newList, prevList = [ starter ], [ starter ], [ starter ]\n",
    "    while len(newList) > 0:  #stop looping if no new neighbors found on previous loop\n",
    "        newList = list()\n",
    "        for V in prevList:\n",
    "            for VV in NEIGHBORLIST[V]:\n",
    "                if VV in VLIST and VV not in foundList:\n",
    "                    newList.append(VV)\n",
    "                    foundList.append(VV)\n",
    "        prevList = newList.copy()        \n",
    "    return foundList   \n",
    "\n",
    "def isContiguous(VLIST,NEIGHBORLIST,returnBiggestPiece=False):\n",
    "    \"\"\"\n",
    "    This method determines if all items in a list form a continuous chain of neighbors based on the passed neighborlist\n",
    "    Empty lists are considered contiguous.  If discontiguous, a less-than-majority piece list is returned,\n",
    "     unless giveBig=True, in which case we return the biggest piece\n",
    "    \"\"\"    \n",
    "    isUnbroken, newList, foundList = True, list(), list()\n",
    "    if len(VLIST) > 0:\n",
    "        foundList, newList, prevList = [ VLIST[0] ], [ VLIST[0] ], [ VLIST[0] ]\n",
    "    while len(newList) > 0:  #this round's list of neighbors\n",
    "        newList = list()\n",
    "        for V in prevList:\n",
    "            for VV in NEIGHBORLIST[V]:\n",
    "                if VV in VLIST and VV not in foundList:\n",
    "                    newList.append(VV)\n",
    "                    foundList.append(VV)\n",
    "        prevList = newList.copy()      \n",
    "    pickedPieceList = foundList.copy()  #default contiguous sublist to pass back to main\n",
    "    \n",
    "    if len(foundList) < len(VLIST):  #not contiguous\n",
    "        isUnbroken  = False\n",
    "        pieceLists, remainingList = [foundList], list( set(VLIST).difference(set(foundList) ) )\n",
    "        if returnBiggestPiece == True:  #we were asked for the biggest piece, not a random small one, so we must find them all\n",
    "            if len(foundList) < 0.5*len(VLIST):\n",
    "                while len(remainingList) > 0:\n",
    "                    newList = getContigFromStarter(remainingList[0], remainingList, NEIGHBORLIST)\n",
    "                    pieceLists.append(newList)\n",
    "                    remainingList = list(set(remainingList).difference(set(newList)))\n",
    "                pieceLengths = [len(pL) for pL in pieceLists]\n",
    "                pickedPieceList = pieceLists[ pieceLengths.index(np.max(pieceLengths)) ]\n",
    "            \n",
    "        else: #quickly return a contiguous sub-list that's at most half the total units in the list\n",
    "            if len(foundList) > 0.5*len(VLIST): #pick a different piece; this one is the majority\n",
    "                pickedPieceList = getContigFromStarter(remainingList[0], remainingList, NEIGHBORLIST)\n",
    "                \n",
    "    return isUnbroken, pickedPieceList\n",
    "\n",
    "def enclaveCheck(UNITLIST,UNITNBRS,maxLoops=4):\n",
    "    \"\"\"\n",
    "    This method determines if a list of units has an unbroken boundary AND whether its complement has an unbroken boundary\n",
    "    If the complement boundary is broken, there is an enclave or the district is so disconnected its adjoining units aren't contiguous\n",
    "    The method returns contiguity of boundary and of its adjoiners.  Also returns the lists of boundary and complement-boundary units\n",
    "      If either of these is broken, only a contiguous sublist is returned that is guaranteed to be smaller than half (for finding enclaves)\n",
    "      maxLoops is the number of loops for expanding neighbors-of-neighbors for contiguity of the units outside the passed unit-list\n",
    "    \"\"\"\n",
    "    UNITSET = set(UNITLIST)\n",
    "    ADJLIST =  get2nbrs(UNITLIST, UNITNBRS)  #in case direct adjoiners are only queen-adjacent\n",
    "    #adjoinersOfAdjoiners = getAdjoiners(ADJLIST,  UNITNBRS)\n",
    "    #BDRYLIST = list( set(UNITLIST).intersection(set(adjoinersOfAdjoiners)) )  #this might fail for queen-adjacent boundary units\n",
    "    BDRYLIST = list (set(get2nbrs(ADJLIST,UNITNBRS)).intersection(UNITSET) )  #in case inHD boundary is only queen-adjacent\n",
    "    noEnclave, enclaveList =   isContiguous(ADJLIST, UNITNBRS)  \n",
    "    unbroken, smallPieceList = isContiguous(BDRYLIST, UNITNBRS)\n",
    "    if not unbroken: #could be that district's boundary intersects the state boundary or there is a nonHD enclave inside the HD\n",
    "        unbroken, smallPieceList = isContiguous(UNITLIST, UNITNBRS)  #slower check for full district, not just its boundary \n",
    "    nLoops = 1 #could be that fragmented adjoining districts are underestimating true contiguity.  Widen the contig search\n",
    "    while nLoops <= maxLoops and not noEnclave:\n",
    "        nLoops +=1\n",
    "        newSet = set(ADJLIST)\n",
    "        for UU in ADJLIST:\n",
    "            newSet = newSet.union( set(UNITNBRS[UU]).difference(UNITSET) )\n",
    "        ADJLIST = list(newSet)\n",
    "        noEnclave, enclaveList =   isContiguous(ADJLIST, UNITNBRS)\n",
    "    #isJiggy = noEnclave and unbroken\n",
    "    return unbroken, noEnclave, smallPieceList, enclaveList\n",
    "\n",
    "def avoidedEnclave(UNITLIST, UNITNBRS, ADDLIST,MAXLOOPS=15):  #20 is arbitrary, but does suppress slender chains\n",
    "    \"\"\"\n",
    "    This method (new for WI 5-23-24) is designed as a shorter check than enclaveCheck for legitimacy of adding ADDLIST to UNITLIST\n",
    "    It tries to find contiguity among all ADDLIST's neighbors that won't be in the UNITLIST after the add.\n",
    "    It does this in successive loops, growing from one non-UNITLIST neighbor in loops to all its non-UL neighbors\n",
    "    If success before MAXLOOPS, it returns True (i.e. this list addition avoided forming an enclave), else it returns False\n",
    "        Note that this method will not usually allow a UNITLIST that doesn't currently touch map border to start touching it\n",
    "        (too many loops to go all the way around the UNITLIST to find the complement's connection)\n",
    "    \"\"\"   \n",
    "    willBeInUnitSet = set(UNITLIST+ADDLIST)\n",
    "    nbrsOfADDLIST = set()\n",
    "    for U in ADDLIST:\n",
    "        nbrsOfADDLIST = nbrsOfADDLIST.union(set(UNITNBRS[U]))  #these are the neighbors of the units we plan to add to UNITLIST\n",
    "    nbrsOfADDLIST = nbrsOfADDLIST.difference(willBeInUnitSet)\n",
    "    if len(nbrsOfADDLIST) == 0:\n",
    "        raise Exception(\"ERROR! Attempted to add list\",ADDLIST,\"but it should have been flagged previously as an enclave\")\n",
    "    firstNo = next(iter(nbrsOfADDLIST))  #pick one of these non-UL neighbors as a starter\n",
    "    firstGroup = getContigFromStarter(firstNo, nbrsOfADDLIST, UNITNBRS) #first find all neighbors that directly connect\n",
    "    foundNbrSet, foundTotalSet, newFoundSet = set(firstGroup),set(firstGroup),set(firstGroup)\n",
    "    LOOPNO = 0\n",
    "    stillConnect = False\n",
    "    if len(foundNbrSet) == len(nbrsOfADDLIST):  #ALL non-UNITLIST neighbors still DIRECTLY connect after the add\n",
    "        stillConnect = True\n",
    "    while len(newFoundSet) > 0 and LOOPNO <= MAXLOOPS and not stillConnect:\n",
    "        LOOPNO +=1\n",
    "        lastFoundSet = newFoundSet\n",
    "        newFoundSet = set()\n",
    "        for U in lastFoundSet:\n",
    "            newFoundSet = newFoundSet.union(set(UNITNBRS[U]))\n",
    "        newFoundSet = newFoundSet.difference(willBeInUnitSet)\n",
    "        \n",
    "        foundTotalSet = foundTotalSet.union(newFoundSet)\n",
    "        foundNbrSet = foundTotalSet.intersection(nbrsOfADDLIST)  #running list of complement-connectable non-UL neighbors of ADDLIST\n",
    "        if len(foundNbrSet) == len(nbrsOfADDLIST):  #ALL non-UNITLIST neighbors still connect after the add\n",
    "            stillConnect = True\n",
    "    return stillConnect\n",
    "              \n",
    "\n",
    "def avoidedIsland(UNITLIST, UNITNBRS, SHEDLIST,MAXLOOPS=15):\n",
    "    \"\"\"\n",
    "    analogous to avoidedEnclave but for shedding a list from UNITLIST; we look to connect in-UNITLIST neighbors after the proposed shed\n",
    "    \"\"\"\n",
    "    shrunkSet = set(UNITLIST).difference(set(SHEDLIST))  #shorthand for the proposed unitlist after shedding\n",
    "    nbrsOfSHEDLIST = set()\n",
    "    for U in SHEDLIST:\n",
    "        nbrsOfSHEDLIST = nbrsOfSHEDLIST.union(set(UNITNBRS[U]))\n",
    "    nbrsOfSHEDLIST = nbrsOfSHEDLIST.intersection(shrunkSet)\n",
    "    if len(nbrsOfSHEDLIST) == 0:\n",
    "        raise Exception(\"ERROR! Attempted to shed list\",SHEDLIST,\"but it was never connected to the rest of the unit list\")\n",
    "    firstNo = next(iter(nbrsOfSHEDLIST))  #pick one of these still-in-UL neighbors as a starter   \n",
    "    firstGroup = getContigFromStarter(firstNo, nbrsOfSHEDLIST, UNITNBRS) #first find all neighbors that directly connect\n",
    "    foundNbrSet, foundTotalSet, newFoundSet = set(firstGroup),set(firstGroup),set(firstGroup)\n",
    "    LOOPNO = 0\n",
    "    stillConnects = False\n",
    "    if len(foundNbrSet) == len(nbrsOfSHEDLIST):  #ALL in-UNITLIST neighbors of the shedlist still DIRECTLY connect after the shed\n",
    "        stillConnects = True\n",
    "    while len(newFoundSet) > 0 and LOOPNO <= MAXLOOPS and not stillConnects:\n",
    "        LOOPNO +=1\n",
    "        lastFoundSet = newFoundSet\n",
    "        newFoundSet = set()\n",
    "        for U in lastFoundSet:\n",
    "            newFoundSet = newFoundSet.union(set(UNITNBRS[U]))\n",
    "        newFoundSet = newFoundSet.intersection(shrunkSet)\n",
    "        \n",
    "        foundTotalSet = foundTotalSet.union(newFoundSet)\n",
    "        foundNbrSet = foundTotalSet.intersection(nbrsOfSHEDLIST)\n",
    "        if len(foundNbrSet) == len(nbrsOfSHEDLIST):  #all in-UNITLIST neighbors still connect after the shed\n",
    "            stillConnects = True\n",
    "    return stillConnects\n",
    "\n",
    "def getBdryNonEdgers(UNITLIST, UNITNBRS): #all in-district boundary units that neighbor a non-district unit\n",
    "    ALLnonHDnbrs = set()\n",
    "    for UUU in UNITLIST:\n",
    "        ALLnonHDnbrs = ALLnonHDnbrs.union(set(UNITNBRS[UUU])).difference(set(UNITLIST))\n",
    "    BdryNonEdgerSet = set()\n",
    "    for UUU in UNITLIST:\n",
    "        if len(set(UNITNBRS[UUU]).intersection(ALLnonHDnbrs)) > 0:\n",
    "            BdryNonEdgerSet.add(UUU)\n",
    "    return list(BdryNonEdgerSet)\n",
    "\n",
    "def getEnclaveLists(UNITLIST, UNITNBRS):\n",
    "    \"\"\"\n",
    "    finds ALL units enclaved by a UNITLIST, parsed into lists of contiguous pieces\n",
    "    We assume the largest contiguous complement to the UNITLIST is not an enclave, but rather the majority of the HD complement\n",
    "    if the UNITLIST's complement (all couldBeEnclaved) is contiguous, the returned list will be blank\n",
    "    \"\"\"\n",
    "    eSets, nU = list(), len(UNITNBRS)\n",
    "    offmapList = list()\n",
    "    for i,L in enumerate(UNITNBRS):\n",
    "        if len(L) == 0:\n",
    "            offmapList.append(i)  #offmap list are units with no neighbors (were surrounded)\n",
    "    complementSet = set([i for i in range(nU)] ).difference( set(UNITLIST + offmapList) )    \n",
    "    remaining2nbrs = get2nbrs(UNITLIST, UNITNBRS)\n",
    "    \n",
    "    isContig, shortList = isContiguous(remaining2nbrs,UNITNBRS) #quicker than contig check on entire complement\n",
    "    while not isContig:  #this will kick out before writing the final sublist = map majority\n",
    "        starter = shortList[0]\n",
    "        newEnclaveList = getContigFromStarter(starter, list(complementSet), UNITNBRS)\n",
    "        eSets.append(set(newEnclaveList))\n",
    "        remaining2nbrs = list(set(remaining2nbrs).difference(set(shortList)) )\n",
    "        isContig, shortList = isContiguous(remaining2nbrs,UNITNBRS)\n",
    "        \n",
    "        # couldBeEnclaved = list( set(couldBeEnclaved).difference(set(newEnclaveList)) )  #revised 18-Feb-24 -- was slower\n",
    "    fused_eSets = set()\n",
    "    for i, eSet in enumerate(eSets):\n",
    "        fused_eSets = fused_eSets.union(eSet)\n",
    "        for j in range(i+1, len(eSets) ) :\n",
    "            eSets[j] = eSets[j].difference(eSet)  #in case contiguity occurs, but not in 2-neighbor list; avoid double-count\n",
    "    remnant_eSet = complementSet.difference(fused_eSets) \n",
    "    eLengths = [len(eSet) for eSet in eSets]\n",
    "    if len(eSets) > 0:\n",
    "        if len(remnant_eSet) < np.max(eLengths):  #exchange the small remnant for the biggest found \"enclave\" (usually the major complement) \n",
    "            eSets[eLengths.index(np.max(eLengths))] = remnant_eSet.copy()\n",
    "    eLists = [list(eSet) for eSet in eSets]\n",
    "    return eLists\n",
    "\n",
    "def wontEnclave(proposedU, dList, NBRLIST, mapBDRYLIST):\n",
    "    \"\"\"\n",
    "    This method checks if adding a proposedU to a dList (list of units in a district) will create an \"enclave\" of units in the dList's complement\n",
    "    via two problems:  A) the dList will now have a discontiguous set of units on the map boundary.  The full map boundary list is mapBDRYLIST\n",
    "      B) The non-dList neighbors of dList units aren't contiguous\n",
    "    The method doesn't require that the dList wontEnclave without the proposedU included; it just checks the proposedU + dList combination\n",
    "    It also doesn't check that the dList is itself contiguous with or without proposedU\n",
    "    In that sense, it is more limited than enclaveCheck\n",
    "    \"\"\"\n",
    "    wontEnclave = True\n",
    "    newList, newSet = dList + [proposedU], set(dList + [proposedU])\n",
    "    unitsOnBoundary = list( set(mapBDRYLIST).intersection(newSet) )\n",
    "    wontEnclave, __ = isContiguous(unitsOnBoundary,NBRLIST)  #first check - does district touch MAP boundary in multiple places? (quick FAIL)\n",
    "    if wontEnclave: #slower check below for internal enclaves\n",
    "        adjoiners = get2nbrs(newList, NBRLIST)  #2-level to protect for queen adjacency in boundary        \n",
    "        wontEnclave, __ = isContiguous(adjoiners,NBRLIST)\n",
    "        if not wontEnclave:\n",
    "            nLoops = 1 #could be that fragmented adjoining districts are underestimating true contiguity.  Widen the contig search\n",
    "            maxLoops, ADJLIST = 6, adjoiners #unlike enclaveCheck, here we just arbitrarily set a number of loops for search expansion\n",
    "            while nLoops <= maxLoops and not wontEnclave:\n",
    "                nLoops +=1\n",
    "                adjSet = set(ADJLIST)  #align nomenclature w enclaveCheck\n",
    "                for UU in ADJLIST:\n",
    "                    adjSet = adjSet.union( set(NBRLIST[UU]).difference(set(newList)) )\n",
    "                ADJLIST = list(adjSet)\n",
    "                wontEnclave, __ =   isContiguous(ADJLIST, NBRLIST)\n",
    "        \n",
    "    return wontEnclave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d041d328-83e0-45db-a869-e0956c23ee26",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter the state postal code; e.g. OH  IL\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, enter 1 below to use il_pl2020_vtd.dbf as this state's population data file\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "  1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "attempting to read in state unit geometries.  Stand by ...\n",
      "I read in the Census popn data. IL has 12812508 peeps and is divided into 10084 shapes.\n"
     ]
    }
   ],
   "source": [
    "STATE = str(input(\"Enter the state postal code; e.g. OH \")).upper()\n",
    "popFilename = STATE.lower()+\"_pl2020_vtd.dbf\"\n",
    "print(\"OK, enter 1 below to use\",popFilename,\"as this state's population data file\")\n",
    "enter1 = input(\" \")\n",
    "if int(enter1) != 1:\n",
    "    popFilename = input(\"OK, then enter the pop data file.  Typically a xx_pl2020_vtd.dbf\")\n",
    "print(\"attempting to read in state unit geometries.  Stand by ...\")\n",
    "tractPopFile = gpd.read_file(\"state_map_files/\"+popFilename)\n",
    "trueTractGeom = tractPopFile['geometry']\n",
    "nTracts = len(trueTractGeom)\n",
    "tractPop = tractPopFile['P0010001']\n",
    "statePop = np.sum(tractPop)\n",
    "censusGEOID20 = tractPopFile['GEOID20']\n",
    "print(\"I read in the Census popn data.\",STATE,\"has\",statePop,\"peeps and is divided into\",nTracts,\"shapes.\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3bfdea9d-b0ea-497a-a556-6b488a3e333e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter the number of districts in the state.  My guess is 17 17\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There appear to be 102 counties in IL .  I will assign them county Nos 0 - 101\n"
     ]
    }
   ],
   "source": [
    "tractGeom = trueTractGeom.copy()   #for some states, we will modify geom, so preserve original\n",
    "#tractNAME20 = tractPopFile['NAME20']\n",
    "tractPop = tractPopFile['P0010001']\n",
    "inputfileCountyNo = tractPopFile['COUNTYFP20']\n",
    "vtdGEOID20 =  tractPopFile['GEOID20'] \n",
    "nDistricts = int(round(statePop/760000,0))\n",
    "nCutDistricts = 0\n",
    "nDistricts = int(input(\"Enter the number of districts in the state.  My guess is \"+str(nDistricts)))\n",
    "tractArea = [tractGeom[t].area for t in range(nTracts)]\n",
    "trueTractCP =   [tractGeom[t].centroid for t in range(nTracts)]\n",
    "tractCP = trueTractCP.copy()  #for some states, we move secluded corners into the map, so save the true data\n",
    "tractCPx =  [tractCP[t].x for t in range(nTracts)]\n",
    "tractCPy =  [tractCP[t].y for t in range(nTracts)]\n",
    "inputCountyNumbers = list()\n",
    "for t in range(nTracts):\n",
    "    if inputfileCountyNo[t] not in inputCountyNumbers:\n",
    "        inputCountyNumbers.append(inputfileCountyNo[t])\n",
    "nCounties = len(inputCountyNumbers)\n",
    "print(\"There appear to be\",nCounties,\"counties in\",STATE,\".  I will assign them county Nos 0 -\",int(nCounties-1))\n",
    "sortedICNs = list(np.sort(inputCountyNumbers))\n",
    "countyNo = [sortedICNs.index(inputfileCountyNo[t]) for t in range(nTracts) ]\n",
    "\n",
    "isSkippedTract = [0] *nTracts  #this will house a temporary list of tracts for manipulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "adffc7a4-a78c-477f-8ea4-7f8e5109fa2a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will now build the county-by-county geometries, hoping there are no islands\n",
      "Building county geom for county 0\n",
      "Building county geom for county 20\n",
      "Building county geom for county 40\n",
      "Building county geom for county 60\n",
      "Building county geom for county 80\n",
      "Building county geom for county 100\n",
      "Here is your original county-based map b4 any triage; e.g eliminating coastal unpopulated tracts w pop < 4.5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There appear to be 2 unpopulated coastal tracts.\n",
      "Lets plot them and their parent counties\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"We will now build the county-by-county geometries, hoping there are no islands\")\n",
    "skipList = list()  #a list of units we previously know to skip in the map\n",
    "isAlteredCounty = [False for c in range(nCounties)]\n",
    "countyTractList = [list() for c in range(nCounties)]\n",
    "countyPop =       [0. for c in range(nCounties)]\n",
    "countyGeom =      [dummyPoly for c in range(nCounties)]\n",
    "for t in range(nTracts):\n",
    "    if t not in skipList:\n",
    "        c = countyNo[t]\n",
    "        countyTractList[c].append(t)\n",
    "        countyPop[c] += tractPop[t]\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"Building county geom for county\",c)\n",
    "    for t in countyTractList[c]:\n",
    "        if countyGeom[c] == dummyPoly:\n",
    "            countyGeom[c] = tractGeom[t]\n",
    "        else:\n",
    "            countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "origMAP = countyGeom[0]\n",
    "for c in range(nCounties):\n",
    "    origMAP = origMAP.union(countyGeom[c])\n",
    "    if countyGeom[c] == dummyPoly:\n",
    "        print(\"WARNING! county\",c,\"is empty!\")\n",
    "    else:\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c,countyGeom[c])\n",
    "minTractPop = 4.5\n",
    "print(\"Here is your original county-based map b4 any triage; e.g eliminating coastal unpopulated tracts w pop <\",minTractPop)\n",
    "plt.show()\n",
    "if origMAP.geom_type == dummyPoly.geom_type:\n",
    "    mapExterior = origMAP.exterior\n",
    "else:\n",
    "    for i,geo in enumerate(origMAP.geoms):\n",
    "        if i == 0:\n",
    "            mapExterior = geo.exterior\n",
    "        else:\n",
    "            mapExterior = mapExterior.union(geo.exterior)\n",
    "\n",
    "for c in range(nCounties):\n",
    "    for t in countyTractList[c]:\n",
    "        if tractPop[t] < minTractPop:\n",
    "            if tractGeom[t].intersects(mapExterior):\n",
    "                isAlteredCounty[c] = True\n",
    "                skipList.append(t)\n",
    "print(\"There appear to be\",len(skipList),\"unpopulated coastal tracts.\")\n",
    "if len(skipList) > 0:\n",
    "    print(\"Lets plot them and their parent counties\")\n",
    "    for t in skipList:\n",
    "        plotPoly(tractGeom[t])\n",
    "        plotCenter(t,tractGeom[t],6)\n",
    "    plotPoly(origMAP,0.2)\n",
    "    for c in range(nCounties):\n",
    "        if isAlteredCounty[c]:\n",
    "            plotPoly(countyGeom[c])\n",
    "    plt.show()\n",
    "trueMAP = origMAP  #use these terms interchangeably"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7a6c93c4-af08-47d5-90f7-dc0b4513aad5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Last chance to alter the skipList, otherwise the above 2 units will be axed\n",
      "here is the proposed skipList [4895, 4854]\n",
      "here is the final skipList [4895, 4854]\n"
     ]
    }
   ],
   "source": [
    "print(\"Last chance to alter the skipList, otherwise the above\",len(skipList),\"units will be axed\")\n",
    "print(\"here is the proposed skipList\", skipList)\n",
    "#skipList = [146, 3084] #...  #alter here if needed - nothing for MO\n",
    "print(\"here is the final skipList\", skipList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2989f381-466b-4882-bf1d-cfa37a7ba8ef",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I will now preserve the original county unit lists and geoms, then rebuild as needed\n",
      "removing coastal units from countyNo 15\n",
      "removing coastal units from countyNo 48\n",
      "Here is the revised state county map after eliminating coastal tracts\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Excellent!  We have no populated islands.  SKIP the below code block.\n",
      "we will scale longitudinal distance by 0.766\n"
     ]
    }
   ],
   "source": [
    "print(\"I will now preserve the original county unit lists and geoms, then rebuild as needed\")\n",
    "trueCountyTractList = [list() for c in range(nCounties)]\n",
    "trueCountyGeom = [countyGeom[c] for c in range(nCounties)]\n",
    "for c in range(nCounties):\n",
    "    trueCountyTractList[c] = countyTractList[c].copy()\n",
    "    if isAlteredCounty[c]:\n",
    "        print(\"removing coastal units from countyNo\",c)\n",
    "        countyTractList[c] = list()\n",
    "        countyGeom[c] = dummyPoly\n",
    "        for t in trueCountyTractList[c]:\n",
    "            if t not in skipList:\n",
    "                countyTractList[c].append(t)\n",
    "                if countyGeom[c] == dummyPoly:\n",
    "                    countyGeom[c] = tractGeom[t]\n",
    "                else:\n",
    "                    countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "        if countyGeom[c] == dummyPoly:\n",
    "            print(\"Uh oh! county\",c,\"didn't have any usable tracts\")\n",
    "MAP = countyGeom[0]\n",
    "for c in range(nCounties):\n",
    "    plotPoly(countyGeom[c])\n",
    "    plotCenter(c,countyGeom[c])\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "origPopMAP = MAP   #origPopMAP is the map after eliminating coastal unpopulated tracts, with original islands\n",
    "print(\"Here is the revised state county map after eliminating coastal tracts\")\n",
    "plt.show()\n",
    "if MAP.geom_type == dummyPoly.geom_type:\n",
    "    print(\"Excellent!  We have no populated islands.  SKIP the below code block.\")\n",
    "else:\n",
    "    print(\"We appear to have some populated islands.  Separate out the main state geom in next block.\")\n",
    "LAT = MAP.centroid.y\n",
    "xScale = (1. - 1.089* abs(LAT/90)**1.9)\n",
    "print(\"we will scale longitudinal distance by\",r5(xScale))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8a562a21-4107-4a3c-a320-90442a473387",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets first identify which county each island belongs to.  Then we'll move the island to the closest county mainland\n",
      "unit 3739 is a true island.  We will move it to adjoin the mainland in same county.\n",
      "unit 3759 has island pieces.  We will reduce the tract to its main state component\n"
     ]
    },
    {
     "data": {
      "image/png": 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lqC1zgIR1QP/ZwNCFd509nIioObFSQ2QPBAFQamotGuxfVr82DAYg+XvjHVhDX7vr5kRE1ow/yYhasp5TgIjrc5+V6kRUVtZjwLxze4DyfKBjjLkjIyJqdkxqiFoyQQBCRwEAlh+uwIeHKpCXl1e3fUUR2FlVnQns00QBEhE1H15+ImrpnI2zf2cWG5CWJ+LatWvw8rphRvCyPGDrC0DmMcCzA+DTGUjdBWQdBwbMqddAf0RE1opJDVFLFxQJse9MLMByjA+VQ370U8Dlb0BRlrHPTd4FYN/bxsQm+B7gzC/AqZ+ADsOBSd8CHYZa+giIiMyCdz8R2YihbWV4uo8DxoQqIIGh9so2g4BR7wJeHYGSXOM0DAoXywRKRFQPvPuJyA6dFdrgga9SsWHNu5g4oi+gbgWU5gJyJ8C9zfUNnT0tFyQRURNiUkNkI3z9fHHubCoy88uAVj2MC1U+lg2KiKgZ8e4nIhvh42WswDR6pm4iohaKSQ2Rjaie1LLRM3UTEbVQTGqIbISHhwcAVmqIyH4xqSGyEdVJzZUruRaOhIjIMpjUENmI6stP2VcaMFM3EZENYFJDZCOqKzUXzp+3bCBERBbCpIbIRlRXakqKiywcCRGRZTCpIbIR1ZUaAKioqLBgJERElsGkhshGVFdqAN7WTUT2iUkNkY2omdTwtm4iskdMaohshKOjo+k5KzVEZI+Y1BDZEAeFAgArNURkn5jUENmQ1m3aAmClhojsE5MaIhvi62OclZuVGiKyR0xqiGyId9VM3azUEJE9YlJDZEOq74BipYaI7BGTGiIbUj0AHys1RGSPmNQQ2ZDqSk0OZ+omIjvEpIbIhlRXarKysi0cCRFR82NSQ2RDqis158+ftXAkRETNj0kNkQ2prtRU6nQWjoSIqPkxqSGyITXnfyotLbVgJEREzY9JDZENqa7UALytm4jsD5MaIhvi5uZmes7buonI3jCpIbIhDg4Opues1BCRvWFSQ2RjVGoNAFZqiMj+MKkhsjHBrdsAYFJDRPaHSQ2RjfHxNk5qyctPRGRvGpXULFmyBIIg4NlnnzUtW7lyJaKioqBWqyEIAvLz8+/azuuvvw5BEGo9QkNDa20TFRV10zYzZ85sTPhENsmT8z8RkZ2SNXTH+Ph4rFixAhEREbWWl5aWIiYmBjExMYiNja1ze507d8auXbuuBya7ObTp06dj4cKFptdOTk4NiJzItlXf1s1KDRHZmwYlNcXFxZg0aRJWrVqFRYsW1VpXXbXZs2dP/QKRyeDr63vHbZycnO66DZG9qx6ALzeXlRoisi8Nuvw0a9YsjB49GkOHDjVbIGfOnIG/vz/atm2LSZMm4eLFizdts379enh6eiI8PByxsbF3HDFVq9WisLCw1oPIHlRXanJ5+YmI7Ey9KzUbN27EkSNHEB8fb7Yg+vbti08//RQhISHIzMzEggULMHDgQJw4cQIqlQoA8OijjyI4OBj+/v44fvw45s+fj5SUFGzevPmWbS5evBgLFiwwW4xELUV1peZyRoaFIyEial71SmrS09MxZ84c7Ny5E0ql0mxBjBw50vQ8IiICffv2RXBwML7++mtMmzYNADBjxgzTNl26dIGfnx+io6ORlpaGdu3a3dRmbGws5s2bZ3pdWFiIwMBAs8VMZK2qKzUXz5+zcCRERM2rXklNQkICcnJy0KNHD9MyvV6Pffv24cMPP4RWq4VUKm10UK6urujYsSNSU1Nvu03fvn0BAKmpqbdMahQKBRQKRaNjIWppak5qKYoiBEGwYDRERM2nXn1qoqOjkZSUhMTERNOjV69emDRpEhITE82S0ADGjshpaWnw8/O77TaJiYkAcMdtiOxRzUkti4qKLBgJEVHzqlelRqVSITw8vNYyZ2dneHh4mJZnZWUhKyvLVGVJSkqCSqVCUFCQ6RdkdHQ0xo0bh9mzZwMAnn/+eYwZMwbBwcHIyMjAa6+9BqlUiokTJwIA0tLSsGHDBowaNQoeHh44fvw45s6di0GDBt10SzmRvbtxpm61Wm3BaIiImo/ZRxRevnw5unfvjunTpwMABg0ahO7du+PHH380bZOWlobc3FzT60uXLmHixIkICQnBQw89BA8PD8TFxcHLywuAcZK+Xbt2Yfjw4QgNDcVzzz2HCRMmYMuWLeYOn6jFc3V1NT3nAHxEZE8EURRFSwfRHAoLC6HRaFBQUMBfrmTzqvvR/PLLLxg2bJiFoyEiarj6fH9z7iciG+ThaaxyslJDRPaESQ2RDQoKCgbAqRKIyL4wqSGyQV5enNSSiOwPkxoiG+Tl6QmASQ0R2RcmNUQ2qHr4BF5+IiJ7wqSGyAaZJrWsMXQCEZGtY1JDZIOqKzU5ubz8RET2g0kNkQ2qrtRcunTJwpEQETUfJjVENqg6qcnOzLBwJEREzYdJDZENqjlTt8FgaLL3sZMByYmohajXhJZE1DLUnNSyoKAAbm5uZm1fFEUcyDwAnV4HESKiAqPM2j4RUUOwUkNkg2pWasw9Vo0oith+fjs6uXeCv4s/Orh1MGv7REQNxaSGyAZpNBrTc3MnNSdyT6C3b2+4Kl2RWZKJVi6tzNo+EVFDMakhskHVs3QD5h2Ar7yyHFmlWfB0NI5YXGmoNFvbRESNxT41RC2MTq9DaWUpskqycKXsimm5KIrwc/ZDa01ryCQy+LUKQOblS2at1JwtOIvu3t0BAKfzTqOjW0eztU1E1FhMaohaiEpDJeIy46A36OGqdIWvky86unU0VWVEUURmSSYOZByAg9QBAQHGpMaclZqc0hx0cOuASkMlLhRewLDgYWZrm4iosZjUELUAmcWZSMpNwr2B90IhVdxyG0EQ4O/iD38Xf1wuvgxVuBMccx3NUqnRG/TYe2kvWqtb42z+WWQUZ2Bgq4GNbpeIyJyY1BBZucScRIgQMbz18Drv08qlFQJ0AVD4KnBcdrxR738i9wSyS7IxoNUAKGVK/HH5DwwOGtyoNomImgI7ChNZucKKQlM/lvpw8nWCNkOLgsqCBr2vVq/FjvM74K50R3RwNJQyJQDAIDbdYH5ERI3BSg2RlRMg3H2jW5B4SVB2vgyyOHm99xVFEb+c/wUj24yETHL9n4kzeWfg4+TToHiIiJoaKzVENirUORSaPhrkXLly941vcOzKMfT3718roblYeBEF2gKEuIeYM0wiIrNhUkNko3w8fFB4tBBXPHKQX55f5/0ScxKhF/XwcPSotfx84Xn08u1l5iiJiMyHl5+IrFzNgfTqw93dHWKFiIxdl3Em/wxKdCWI9I+87d1TFwsv4nTeaYR7hsPX2bfWOlEU2ZeGiKwekxoiK3at/Bpc5C4N2rfmpJbdPbvDIBiQkJ0AnUEHiXC9SCtAQKWhEn4ufhgaPPSWbZ26dgqh7qENioOIqLkwqSGyMh8nfowQtxBEB0fjaM5RDAkc0qB2ak5qmZeXBy8vL0T6RzaorbaubRGfFX9TBYeIyJqwTw2RlXmy65O4VHwJW9K2oLW6dYMvP9Ws1DR2AD6FVAEnmROSc5Mb1Q4RUVNiUkNkhQJcAjAoYBDaubZrcBvOzs6m5+aYKqGHTw9o9VpkFmc2ui0ioqbAy09EViQ1LxXnC8+jt29vaBSaRrVVs8JjrkktyyvLTTN0ExFZG1ZqiKzAuYJz+PXir5BJZBgaPLTRCU211m2MlR5zTWpZpi+DXFr/wfyIiJoDkxoiC9Ib9Pj14q+oNFQiOigarTWtzdq+n78fAPNUas4XnEewKrjR7RARNRUmNUQWcq38GnZe2IkB/gPQwa1Dk7zHhXNnAQBLly6FKIqNaqt67iciImvFpIbIQpJzkxHTJqbJkoUDBw4gIyMDAHDp0iXs2rWr0W0awAH4iMh6MakhspB8bX6Tth8cbLxU5NihHwCgffv2jWrPRe6CEl1Jo+MiImoqTGqILCRQFYj0ovQma9/f3x9Rg4eg7EwcVGoNWrdu3aj2XBxcUFxRbJ7giIiaAJMaIgvp5t0NeeV52HlhJyr0FU3yHk88/hgAoEePHg0exK+mmtMrEBFZG/4LRWRBEV4R6OfXD/su7UNcZpzZR+wdP348vLx9ED1ksFnaK68sN0s7RERNQRAbe0tEC1FYWAiNRoOCggKo1WpLh0N0k/zyfFwuuQwnmRPaaNpYOpxbyi7JxrErx3Bv4L23ne2biMic6vP9zUoNkZVwVbqis0dnXCi8gAJtgaXDuSUfZx8MCRqC3em7LR0KEdFNGpXULFmyBIIg4NlnnzUtW7lyJaKioqBWqyEIAvLz8+/azuuvvw5BEGo9QkNDa21TXl6OWbNmwcPDAy4uLpgwYQKys7MbEz6RVbo34F4cv3IcFwov4Gz+WRRoC1CgLWj0ODPmkF2SjT8v/wl/Z39Lh0JEdJMGz/0UHx+PFStWICIiotby0tJSxMTEICYmBrGxsXVur3PnzrXG0ZDJaoc2d+5c/Pzzz9i0aRM0Gg1mz56N8ePH488//2zoIRBZJUEQMKDVAGw9txURnhFIy0+DTCIz3QIuwNjhVyFVIMQ9xGxTKtzNd2e+Q5hHGAYGDGSHYSKySg1KaoqLizFp0iSsWrUKixYtqrWuumqzZ8+e+gUik8HX1/eW6woKCrBmzRps2LABQ4YMAQCsXbsWYWFhiIuLQ79+/ep9DETWTCJIcF/b+wAAQeqgW25TVlmGlGspyNfmo5VLK7TVtIVUIm2SeNKL0tHRvSNC3UPvvjERkYU06OfWrFmzMHr0aAwdOtRsgZw5cwb+/v5o27YtJk2ahIsXL5rWJSQkQKfT1Xq/0NBQBAUF4cCBA2aLgaglcZQ5opt3N0QFRmHbuW34M+NP/HH5D2w/tx0nr56EQTTf6L+peano7NHZbO0RETWFeldqNm7ciCNHjiA+Pt5sQfTt2xeffvopQkJCkJmZiQULFmDgwIE4ceIEVCoVsrKy4ODgAFdX11r7+fj4ICsr65ZtarVaaLVa0+vCwkKzxUtkbZ7p8Yzpud6gx9Xyq/j57M8YFjwMKXkpCHUPbdDdSgbRgN3puxHiFmLOcImImkS9KjXp6emYM2cO1q9fD6XSfPPVjBw5Eg8++CAiIiIwYsQIbN26Ffn5+fj6668b3ObixYuh0WhMj8DAQLPFS2TNpBIpvJ280du3N17981UUagtxMPNgg9r69eKviPSLRIAqwMxREhGZX72SmoSEBOTk5KBHjx6QyWSQyWTYu3cvPvjgA8hkMuj1erME5erqio4dOyI1NRUA4Ovri4qKipvupMrOzr5tP5zY2FgUFBSYHunpTTccPZE1cpA6oJNHJ4gQTZ2L60MURSikCjjJnZogOiIi86tXUhMdHY2kpCQkJiaaHr169cKkSZOQmJgIqdQ8nRSLi4uRlpYGPz8/AEDPnj0hl8vx66+/mrZJSUnBxYsXERkZecs2FAoF1Gp1rQeRPXFXuiPEPQTOcmc4y53rvf/x3OMI9wxvgsiIiJpGvfrUqFQqhIfX/kfO2dkZHh4epuVZWVnIysoyVVmSkpKgUqkQFBQEd3d3AMbkaNy4cZg9ezYA4Pnnn8eYMWMQHByMjIwMvPbaa5BKpZg4cSIAQKPRYNq0aZg3bx7c3d2hVqvx9NNPIzIyknc+Ed2Br7MvFFIFWrm0qtd+oijibP5ZdPXq2kSRERGZX4PHqbmd5cuXY8GCBabXgwYNAmC8BXvKlCkAgLS0NOTm5pq2uXTpEiZOnIirV6/Cy8sL99xzD+Li4uDl5WXaZunSpZBIJJgwYQK0Wi1GjBiBjz/+2NzhE9kUXydf7EnfAz9nv9uOLVOgLcDh7MMQIKCVSytcLb+KssoyRAVGNWusRESNxbmfiGxccUUx4rPiIZPIEOEVAQepA9Lzc/HHKS0C/LPhINfh3oB7IQgCzhech7+LPxykDpYOm4gIQP2+v81eqSEi6+Li4ILBQYNRaajEidwTOHwhF8t/y0ReRS4eCOuHd/8WZdq2taa1xeIkImosjnVOZCdkEhnOXPTAom+16OQVgkfCh2LrsQIUlOksHRoRkVkwqSGyE6ezi/DqDyfwUK8ArJvaG3OGdoBOb8C3CZcsHRoRkVkwqSGycaIo4uyVYjy04gDcnRyw4P5wCIIAb5USMeG++CLuAgwGu+haR0Q2jkkNkQ0zGETM2ZiIIe/uRX6pDs9Ed4Cjw/XxpKYOaI2zuSX44dhlC0ZJRGQeTGqIbFhusRY/HsvAqC6+OPRSNB7pU3vG757B7hgd4Yc3t55CsbbSQlESEZkHkxoiG+atViKyrQd0ehHe6lvP1/bSqDAUl1fiza1/NXN0RETmxaSGyMZpHOXQVhpuu76VqyNeHh2GDQcvYufJ7GaMjIjIvJjUENk4P1clLl4tueM2k/oGYWiYN1745hiyCsqbKTIiIvNiUkNk43oGu+H81VL8lVl4220EQcDbf+sKB5kEc79KhJ53QxFRC8SkhsjGDe/ki3Zezpj5RQLOXim+7Xbuzg5Y+nA3xJ27iuV705oxQiIi8+DcT0R2IP1aKSatPoj0vFL0DnZHkIcT/DVKDO/si/BWmlrbvrPjFJbvPYtNMyPRI8jNQhETERnV5/ubSQ2RnSjX6fFD4mXsSbmCrMJypOYUQ6szYOo9rTFzUDu4ORsnsdTpDXhoxQHkFmvx8zMDoVbKLRw5EdkzJjW3wKSmYURRRKVBhFx6/UplwoU8TFwVhy+n90PPYP6Sb6m0lXq88fNf+DzuAnoGuWH99L5QyIwD86VfK8Wo939HVKg3PnikGwRBsHC0RGSv6vP9zT41dEev/ZiMDi9vw4nLBaZloiiiotKAj3enWjAyaiyFTIqFY8Px7ZP9cfxSAV79/gSqf+MEujvhzfFdsOVYBr7h3FBE1EIwqaE7Sr9WCgA4l3v9luCIAFcAwK+nciwREplZjyA3LB7fBV8fvoQvDl40LR/T1R8P9gzAaz8m1/r7JyKyVkxq6I6CPZwBAGUVetMyB9n1j03N5XdSrtNj3+krnDjRSnmpFACAV78/AZ3++kB9r9/fGd4qBf6xLh75pRWWCo+IqE6Y1NAdtXJ1BADkFNUekG1MV38AQNzZq3VqZ/ORy3jik0N4a8cp8wZIZuHkIIWiKln97MAF03JnhQwfPtoDV4q0ePrLo7USHiIia8Okhu7IR2OcLyg15/r4JgaDiLSq16t+P1undoaGeQMAVuw9i/1puWaOkhqrV2t3pCwaicmRwXhr+ymcyS4yrQtvpcGyx3oi7uxV/OeXFAtGSUR0Z0xq6I58qyZBPH7J2FF4a1ImBr2zGyerRqfdn3YVx9Lz79qOt1qJsd2M1Z25XyXyUoaVih0VBj+NEot+rj255YD2nnh2aEes2ncWv53i/FBEZJ2Y1NAdVSc1Z3NLkFdSgafWH8HV4gp8Ma0v3n+kGwBg7Ed/ouIOEyZWu3C1FJ4uDiir0OPfPyQ3ZdjUQEq5FLEjw7D39BXsSandEXzmve0wJNQHT284escpF4iILIVJDd2Rt1pheu7oYBzDZEioN+7p4Imx3Vrhn/e2BQBMWh2H2w15JIoiVv9+Fonp+ejX1gMLx4bjx2MZ+Pl4ZtMfANXbiM4+CG+lvunSolQi4P1HuqG1pzOmfRqPnEJOfElE1oVJDd2RUi41PXeQSjCpbxBOZV3/lR47Mgxjuvoj/nweZnyegP1pufj8wHm8tf0UWr/4Mxb9dBIvf38Ci37+CzPvbYcPHumOsd38MTLcF698n3RTB2SyPEEQ8GifYPyZevWmjuDOChnWTO4NvShi+meH63z3GxFRc2BSQ3V2taQCfdq4I+1KSa0+Mf+b2B0fPtodO09m49FVB/HqD8lYtsc4IeLqP85h85FLWDi2M14cGQqJRIAgCFj0QDikEgEvfpt02woPWc6Yrn4AgEPnrt20zlejxJrJvXE6uxjzvk7kbfpEZDVklg6ArJ9KKUNReSWyC8vRumrcmkt5ZXB1cjBtc1+EPwa298KGQxfRxtMZfdu44+vD6Wjt6YwB7T3hoqj9UfNwUeCtCRGYtu4wvjyUjkf7BjXrMdGdqZRyjO/eCp/8eQ6T+gbBw0VRa314Kw3ef6Qb/vlFAv7zSwpeiAm1UKRERNexUkN31S3QFQCQWVBu6mNzpUh703YaJzmejGqHmHBfuDk74J/3tsOIzr43JTTVosN8MLFPEP7vp5M4n1uCnKJyHEi7itScYpzLLcGx9Hx8m3CJl6gs5KXRYRBF4M2ttx5baHhnX7w0Mgwf70nD14fTmzk6IqKbsVJDdzUy3A+/n8nF94mXUVCmAwD8lVWIwaHejW77ldFh2J+Wi6j/7LntNu29XfDT0/fU6t9DTc/TRYGnotrh3V9O441x4bc8//8Y2AZnc4vx8ndJCHRzQmQ7DwtESkRkxEoN3VV01cB5Px/PRP+qLy293jz9KJwVMqx6ohfae7ugT2t37Jo3CF/N6IeNM/rhh1kD8Nnf++ByXhn+s4ODvtWF3iCatY/SoI5eqNAbbrq9u5ogCFg4Nhx92rhj5hcJOHul+JbbERE1ByY1dFc+aiUe6hUAALj/wz9xb0cv/HLSfAOwdfRRYde8e7FxRj+091ahb1sP9Gvrga6BrhjU0Qv/GNgGXx66iMv5ZWZ7T1tToq3Eq9+fQOfXtmPOxkSzJTahvioEuDliy/HM297pJJdK8PGknvB0ccDjaw4hg39PRGQhTGqoTv7vgXAAQG6xFntPX0Fmgfn7uUgkwi2XTx3QBm7ODrjvg9/x1PoErP3zHPaevoJynf3eTlxRaUBBqfFS4J6UHHRd8Au+ik/HgHae+PFYhtmmMxAEAeO7t8LPxzMxcVXcbbfTOMrx6dQ+AIApaw9xxGgisggmNVQnCpkU+18cYnqdW3xzR+Gm4u7sgE0zI/FQr0BcKdJiwZaTmPzJIczecKTZYjAHg0G8ZQfr+rpWUoHhS/ei56KdmPHZYUxZG49Kg4gfZg/Amim98beeAfhodxqSMwrMEDUwb3gIXh4VhsT0/DuOSxPo7oR1f++D3OIKTP00HiXaSrO8PxFRXTGpoTrzd3XEoZeiAQB927hj58lsvLn1L6w/eAHp10qb9L39NI6IHRWGTTP748irw/B/Yztj11852HzkUpO+rzmIooiPdqdi2NK96P3GLuxq5KW7Lw9dxKW8Mgzr5GO6DPjGuHCE+akBAPNjQtHG0xkTV8bh4lXz/L1UGkQo5RLTqNK3097bBeum9sGZ7GLM2nAE2kr7raYRUfPj3U9UL+U64xxPB89dw8EbBmbb96/BCPJwavIY3J0d8Fi/YMSdu4Yl205hRGdfON/mtnFrsCM5G+/sSMHADp5Iu1KC0npeNqvUGyCTSnAutwQJF/JwIO0qKg0iZgxqi7f+FoErRVq083Ixbe+lUuCV0WGYtu4wjlzMM8vfyYWrJSjXGaA3iJDe5jJhtS4BGix7rAemfXoY//w8AZ9M7n3bS4tEROZkvd8EZJXcnOU3LQtyd8KIzj5o5ebYbHEIgoDYkaEY8u5evP5jMt7+WwQEwTq/ONftP49+bd0xqW8wfj+Ti24BrnXar6hch3//kIwfEi/Dw0VR69JVZ381PF0UUCvlUCtr/53kFJZj3tfH0Ke1O0Z18TPLMfiolXB2kN41oak2sIMXPpjYDU+uP4IFW5Lx+v2drfbvh4hsB5Maqpecqi/Wfw5qi4EdvBDqp4LnDaPNNpcANye8MjoM//4hGc4KGV6/v7NF4riT/NIKHDp/DQvHdsbe01fQ1tP5jpWTc7kl+CYhHX+cycWxSwVwkErQPcgNWQXlmBwZjDA/NR7o3uquY/a4KGT4K7MQ205kYmy3Vo0+jpwiLVp7Otdrn5hwPyx6IBwvf3cCGicHzB3agYkNETUpJjVUZ6IoYt3+83CQSjBnaAc4OVj+4zM4xBtAMtp5u9x1W0v47VQO9AYRQ8N88PHuNAzr5HPL7c7nluBf3xzD4Qt5cHaQwd3ZAU8PaY9RXfxMfWXqylutxLZnB+LV709gzsZEXMorw6zB7QEAheU6qBSyeicXl/JKEdCAStykvsHIL9XhnR0pxsrTfZ2Y2BBRk7H8txK1GBvj0/HZgQt4fUwnq0hoAGPnZU8XBfadvoIHewZY3ajDO09mo2ugK4rKdbicX4Z7Q7xuud2sDUeQnGGc/fzwK0MbfRxqpRzvP9Id/q6OWLrzNALcHCGVCJi94Sg0jnKM696qXpWtS3llGNLAEaRnDW4PtaMcr35/AgCY2BBRk7GObyZqEQ6kXQUATBnQxsKRXCeVCFg4tjPmbDyKh1fG4f2Hu9X7MklTKa2oxN7TVzBrcHv8cSYXMomAvm3cARhv767uPFuircSVIi1kEgHfPTXArInZvGEdkVOoxZyNiQCM48l08HbBp/vPY0xXP3T0UeFKkRbBHs6m/jLfJFzC6ewi+KiV8NcokVlQjnO5JbU6I9fX4/2CAQCvfn8CEkHAK6PDmNgQkdkxqaE6OXoxDzuSszB9oPUkNNVGdfFDgJsjHvjoT0T9Zw++nN7PKuYg+iU5G6UVeoyJ8MfCn06iS4AGTg4yxJ29ikdWxsFfo8QnU3vjX5uOo0RbiZ3z7kUbMydkcqkE/3kwAq3cHLHzZDbemtAFTg5SPLIyDhOWHTBt1zPYDS+NCsW+07l4/9cz8FYpUFCmg7bSeLebIAAPVo0q3VCP9wuGKIr49w/JkAjAS6OY2BCReTVqnJolS5ZAEAQ8++yzpmUrV65EVFQU1Go1BEFAfn5+o9sEgKioKAiCUOsxc+bMxoRPd1Gu02P0B7/jkZUHMGHZfoT6qvDs0I6WDuuWIgJcsf3ZQQjxUWHiqjj8cSbX0iFh24lM9AhyhZdKgT0pObh4tRR7UnJMFZGMgnLEvPc7Ll4rxdczI82e0FQTBAHzhnXEtjkDERHgivbeKsTFRmPzU/3x7oNd8fGkHjiXW4IJyw7gg9/OYE50Bxx6eShO/V8Mjrw6DC/EhOCjR3tALm38sFZPRLbG62M6YdXv57B01xmzzlNFRNTgSk18fDxWrFiBiIiIWstLS0sRExODmJgYxMbGmqXNatOnT8fChQtNr52cmn5MFHv2r2+Om/p5vDEuHA/1CjTLF1tT6eijwurJvTDw7d14bM1BvP9IN9zf1d8i1YCKSgP2p17FtIFt8PuZK6g0iLhaUoEpa+Nx6v9iIBGAtl4uCHRzxNxhHdHZX9Os8cmkEvQIckOPIDcAQFSIF87llsDd2QF+GmOHYEEQ4O7sgKei2pv1vacMaIOSCj3e2ZECvcGA54eHsGJDRGbRoKSmuLgYkyZNwqpVq7Bo0aJa66orLHv27DFbm9WcnJzg6+vbkJCpjorKdVj0018Y1NELW45lAAC+nzUA3QJdLRtYHQW6OyH+5aF4/cdkzNmYiB8SM7DogXD4uzbNGDqiKCL9Whk2H72ExPR8eKsUmDO0I64Wa1GkrUTv1u747ujlWvvM2XgUgiDgjQfC0bet5S+TAYCTg6xZE6vqu7He2ZGCEq0e/76vEwfoI6JGa9DP7lmzZmH06NEYOnSo2QKpS5vr16+Hp6cnwsPDERsbi9LS2w8Br9VqUVhYWOtBNyutqETSpQIkXLiGrUmZGPyfvfjqcDpmVc2r9Oa4Li0moanmpVLgo0k9sOLxnjhxuQDDl+7D53EXYDCY91JHfmkFpn+WgEHv7MaqfWchEQRsOZaJpzccgZ/GEU4OUhw+n4cON9xuviM5Gx9O7G41CY2lzBrcHoseCMe6A+fxyg8nzP73Q0T2p96Vmo0bN+LIkSOIj483WxB1afPRRx9FcHAw/P39cfz4ccyfPx8pKSnYvHnzLbdfvHgxFixYYLYYbY0oivjPLylY++d5lNaYpHBgB0881i8cxy/lY0r/NvBSWWZgPXMY0dkX/dp6YMm2v/Dq9yewJTEDiyd0adRdPNXySirw2JqDuJxfhqUPd8WQUB9oHOX46XgGZm84iiH/2YPSCj3SrhTjg4ndMaC9J97bdRptvVwwvkcrhPrWb+wZW/VYv2A4yCSY/+1xFJdXYunD3eo8ajER0Y3qldSkp6djzpw52LlzJ5RKpVkCqGubM2bMMD3v0qUL/Pz8EB0djbS0NLRr1+6m7WNjYzFv3jzT68LCQgQGBpolZlsQfz4PH+1Ow98HtMGYrn64VlIBF4UMvVq7QyoRMKKzbVzm0zjKsXh8BMZ09Ufs5iSMfP93zInugBmD2jaof1BpRSXW7b+AlfvSIBEEbJzRr1aCcl+EPySCgKfWGytdoyOM0xSEt9Jg9eTe5jkoG/NQr0A4O8jwzMajqKg04MNHu0NmxX23iMh6CWI9bj/4/vvvMW7cOEil18fR0Ov1EAQBEokEWq3WtG7Pnj0YPHgw8vLy4OrqapY2ayopKYGLiwu2b9+OESNG3DX2wsJCaDQaFBQUQK2271/JOr0BT60/gpSsIux5Pspu+jKUVejx3q7TWPX7WbT3dsGMQe0wpqsfFLK6jQuz7/QVzP/2OLIKy/FY32A8GdXutn11rhZrIZUIcHVyMOch2LTtJzIxe8NRRIV44X8Te9x1RnAisg/1+f6uV6UmOjoaSUlJtZZNnToVoaGhmD9//i2Tj6ZqMzExEQDg52eeCftsnd4g4puEdFzOL8efqbk4lp6Pdx/qajcJDQA4OkgROyoMoyP8sHTnaTy/6RiWbPsLD/cOxJiu/ujorbrt+didkoOpa+NxT3tPrP9HX7S9yyUsDwvNh9WSxYT7YdVkKZ764ggeX3MQayb3hsbp5glUiYhup15JjUqlQnh4eK1lzs7O8PDwMC3PyspCVlYWUlNTAQBJSUlQqVQICgqCu7txNNXo6GiMGzcOs2fPrlObaWlp2LBhA0aNGgUPDw8cP34cc+fOxaBBg257+zddtz81F3O+SjTN8hzmp8bGGf3Qq7W7hSOzjIgAV6yd2gdpV4qxbv95fH7gAj7anQaVQob2Pi7wclHAw0UBLxcHeKoUcHVywCd/nEM7L2d8Pq0Pbz9uQoNDvLFhel/8/dN4TFi+H9/O7M/EhojqzOwjCi9fvrxWB91BgwYBANauXYspU6YAMCYpubl1HxzNwcEBu3btwnvvvYeSkhIEBgZiwoQJeOWVV8wauy1KuJCHf3x2GG29nPG/id0R6qviJZEq7bxcsHBsOF4eHYZD567h+KUCnMstQW6xFkmX85FbVIGrJVro9CJ81Ap88Eh3JjTNoHuQG774R19MWn0Qj66Ow5rJveGrMU8fPiKybfXqU9OSWXufmoQLeXj2K+Nkgw90a4XxPQLg7ty45OPP1FzM/CIBYb5qrPt7H/ZRaABRFFFQpoOjg7TOfW/IPP7KLMS0T+OhF0WsfqI3ugQ07wCFRGQd6vP9zaTGCpTr9JiwbD/yS3XoGqjBzpPZEEXgng6eGNXFDyM6+dYqwReU6nDsUj4iAjTQ6UUYRBH703Jx+HwenBykOHD2Ks7nlqJYW4l72nti2WM9oFKyhE8tT05hOaZ/dhins4ux9OFuiAm3jbvyiKjumNTcgrUmNaIoYv63x/F9YgY2P9kf4a00uFZSgZ+OZ+Dn45k4dP4apIKAnsFu6N3aHSqlDJ/uP4/MgvLbttnK1RF927pjeCcfDOvky3E/qEUr1+nx3NfH8HNSJmJHhmLGoLa8DEhkR5jU3II1JjU/JF7GOztScCmvDO/8LQIP9rp5HJ2cwnJsT87C72dyEXf2KorKKzGwgyeeHx6Cs7nFEEVg7Z/nkZFfhkUPhCO7sBwP9w7ipSayKQaDiHd3puCj3Wn4W88ALHogHEo5P+NE9oBJzS1YW1Lz+YHz+PePyRjeyQcTegRgeB0Gu9NXDSPPygvZq02H0/HqDyfQ2V+DZY/1gLeKHYiJbF19vr85bKcFrP79LF79IRlT+7fBskk965TQAMZkhgkN2bMHewXiy+n9kH6tFPf/708cS8+3dEhEZEWY1DSzM9lFWPTzXxjeyQev3hdmV4PfEZlD9yA3bHn6HvhqlHhwxQF8m3DJ0iERkZVgUtPMzuaWAAB6BLuxsyNRA/molfjqn/3wQDd/PLfpGBZsSUal3mDpsIjIwsw++B4ZGQwiDpy9imJtJa6VVOCP1Fw4O0jx9WHjr8pQX5WFIyRq2RQyKd6aEIHwVhos3HISKVlF+PDRHo0e34mIWi52FG4iD684gIPnrtVaFuqrQlF5JZ4a3A6T+gY3eQxE9iLu7FU8tf4InBykWPl4L3Tyt/zNAERkHrz76RaaI6nJKijHgbO5+OSP80i6XAAASHhlKLILtfDTKOHGX5BETeZyfhlmfHYYaVeK8c7fumJMV39Lh0REZtBks3TT7X156CJiN1+fbdxbpcCyx3rCo2pyRCJqWq1cHfHNzP54cfNxPP3lUZzJKca8YR0tHRYRNSNWaszg4z2peHt7CgCgSysNPFwcoKwxT5CIm0/xjWf9xi1u/lsR77j+5v3FO673USnxxrhwyKTsK062RRRFzP0qEd8nZiDtzVEcBoGoheM4Nc2sOoEJ81PDzdkBBhEo0+lNj3KdAdrK2o8KvQG6Go9KvQF6g2h6GEQRYq1H7fcUBEAQBNNDIgimcWykEgEyqQTyGg8HqQQKmfFx4nIBvjqcjoz820+1QNRSCYKAe0O8AAAXr5VaOBoiak6s1NihhAt5mLBsP36ZOwgdfXgXFtmecp0ekYt/hbuzA5Y91pOfc6I7KNfpsWTbKTzWLxjtvV3qtP3yvWmo1It4fkRIk8fHPjV0R45Vc+aUVegtHAlR01DKpVgyIQKLt/6FsR/+iQX3d8bfegZwsEuiWziWno9P95/Hp/vP4x/3tIG7iwMq9WLVlQSxxlUFERWVBsSdvYrL+WUA0CxJTX0wqbFDSrnxqmO5jkkN2a4RnX0xsIMnXvn+BF749jjWHTiPl0aFYUB7T0uHRmRVLlw1XqYd370VdpzMQnF5JWRV3RZkUqFGVwYBMomA/u08IJUI+Dkp08KR34xJjR2qnsG7jEkN2TgnBxn++1A3PNonCG9s/QuTVh/E4BAvvDQqDB14SYrsnMEgIuFiHv7zSwq6Bmjw34e71Xnfzw+cx+Yjl5suuAZiUmOHqjs2l+s4rDzZh16t3bH5yf7YdiILS7adwn3/+wNvjuuCCT0DLB0aUbM7fikfL393An9lFqLSICIiQIPVk3vXqw2lXIqKqptcrOkuWiY1dqi6UsPLT2RPBEHAqC5+GBLqjVe/P4HnNh3DsUv5eGV0JzjIrOcfZaKmtO/0FUxbF48QXxVeGR2G9t4q9GvrXu/ExPQ9UmmAC5MasiSFjH1qyH4p5VK8/bcIdA10xYItyTiZUYiPJ/WAt1pp6dCImtS3CZfw3KZjaO3hhM1PDmhUMl9d8S+r0MNFYT2phPVEQs1GEAQo5RL2qSG7JQgCHusXjDA/NZ78IgH3/e8PPNI7EJUGEc9Ed4BSLr17I0QtQH5pBXan5GBrUhZ2nsxG/3YeeP3+zo2uTlprxZ9JjZ1SyqXsU0N2r2ewG3565h7MWn8EH/yWCgDwUikwdUAbC0dG1HB5JRX45WQWfk7Kwv7UXFQaRGNl8v7OeCIyGILQ+KENqhN/a/txzKTGTjnKpVb3YSSyBG+VEhum98PRi/mYveEIvj96GRN6BkCtlFs6NKJ6Sc0pxtJdp7HjRBb0oog+rd3x2phOGN7ZFz5mvrxqreOdMamxU0q5FFomNUQAALlUgj5t3PHmuC6Y+1UiRizdhzfHd8HgEG9Lh0Z0WwaDiOSMQnx39DJ2JGfhcn4Z/DVKvDI6DKMi/OCtarp+YtY6NAiTGjulZKWG6CZDO/lg+9xBePHb45i6Nh7TB7bBiyPDOCkmWQ2DQcTmo5fxnx0pcFZIkXalBE4OUvytZwAi23pgcKh3s/QJc+TlJ7ImSrnE6jp4EVmDVq6O+OzvfbD2z/NY9PNJnM4uxrsPdYWni8LSoZEdO3IxDxsPXcSBs1eRfs04RcED3fwxb1gIBod6wcmheb/Oq5Oacl5+Imtg7FPDjsJEtyIIAv5+Txu093YxXY56Y1w4RnT2NUsnS6L62H4iC899nQgXpQzDOvlgUAcvRIV4W3R8perLT6VMasgaGO9+sq4PI5G1GdTRCzvmDsJLm5Mw84sjAIA2ns4Y3tkHc6I7NPuvY7IvBaU6vLH1JL4+fAkxnX3xzoMRUFlJB3YHmXEuqJKKSkuHUov1DANIzcqRSQ1RnXi6KLDi8Z54bUwnAIBEAFb/fg793vwVr3yfhIJSnYUjJFsjiiK2JmVi6NK92JaUhcXju2DZYz2sJqGp5qyQoajcupIa/sywUwq5BOVFTGqI6kIQBEwd0MY0fk36tVJ8tDsVX8RdxBdxF7Hn+Si09nS2cJRkC87nlmDBlmTsTrmCoWHeWPRAF/hqrHO0a6kVXoplpcZOcZwaooYLdHfCkgkR+O9DXQEAY/73BzYeugiDQbRwZNRSFZXrsHjbXxi2dC9OZxfjfxO7Y9UTvaw2oQEAnd4AmZXdGchKjZ3iiMJEjTe+RwBCfdX4787TeHFzEj7ek4aewW7oFuiKroGuCPVVccoFuiODQcS3Ry7h7R0pKCrXYfbgDpgxqK2pI641k0klqLSyRJ5JjZ1ylEutbiRIopaok78aqyf3wqFz17A1KRNH0/Px0/EM6PQi1EoZHu4diPBWGvRt42HVv7qp+SVcyMOCLck4fqkA93f1x4sjQ+Hv6mjpsOpMIZNAW2ldP46Z1NgppVwCbSWTGiJz6dPGHX3auAMwTvJ3KqsIW45l4PvEDKz6/RwkAjCwgxcm9w/GkFAfC0dLlpRVUI53dqTg2yOXEN5KjU0zI9G7tbulw6o3hUxidSPTM6mxU0pWaoiajFIuRbdAV3QLdMWr93VCXkkFtidn4av4dPz908N4cWQoZt7bztJhkgV8tDsV7+86A0cHKRaP74KHegW22BGrlXIpKzVkHaqnSRBFkYOJETUxN2cHTOwThEd6B2LpztNYsu0Uissr8dzwjg36/08URRgKCyHI5ZA4OTVBxGRuF66W4I2f/8IvJ7MxY1BbzB7SvsVPmmq8/GRdP45595OdcpRLYRABnd66OnkR2YJly5YhIiICarUaarUakZGR2LZtGwRBwPiOClx46z78KyYUEokEgiCYHps2bTK1UXN59WPjxo0oS05G8e7dqDh/Hu+99hpCgoLg6OiIkJAQfPbZZxY8arqVg2evYuraQ4j6zx4kpufjw0e746VRYS0+oQEAhcz6bjhhpcZOKWtMRmbJobaJbFFAQACWLFmCDh06QBRFrFu3DmPHjsXRo0cRGhqKzMxM/Jh4Ge/sSIGnSoGI4sPYsOpDjBw5slY7a9euRUxMjOm1c1kZxLx8qIYMwbJly/D6ihVYuXIlQq9dwyl3d0yfPh1ubm4YM2ZMcx8y3cBgEPHfnafx4e5UhPmpsWR8F9zftVWLuKuprhRW2DezUd9mS5YsgSAIePbZZ03LVq5ciaioKKjVagiCgPz8/Ea3CQDl5eWYNWsWPDw84OLiggkTJiA7O7sx4ds1RwfjX721dfIisgVjxozBqFGj0KFDB3Ts2BFvvPEGXFxcEBcXB6lUCl9fX8yI6YmdL49FKz8/fLr+a3QeMALOzrUH8HN1dYWvr6/poT92DE49ugMAPv/8c/zzn//EuL59ETp4MB555BHMmDEDb731liUOmWooKtdhxueH8dGeVMyPCcXWZ+7Bw72DbCqhAYyVGq2VVWoanNTEx8djxYoViIiIqLW8tLQUMTExeOmll8zWJgDMnTsXW7ZswaZNm7B3715kZGRg/PjxDQ3f7ill1jltPJGt0ev12LhxI0pKShAZGVlrXWtPZzymTkVFzln01mXg659/r7V+1qxZ8PT0RJ8+ffDJJ59A6uZmWqfVaqFQKKBNOQ1lWBgAwNHREYcOHYJOx6kbLKGgVIdFP53EgCW/Ie7sNXwyuTeejGpns/0WjZUaG0hqiouLMWnSJKxatQpuNf4nA4Bnn30WL774Ivr162e2NgsKCrBmzRr897//xZAhQ9CzZ0+sXbsW+/fvR1xcXEMOwe4pq34xWNv1UCJbkZSUBBcXFygUCsycORPfffcdOnXqVGubv/7Yg7dfexV+bq5o7emOC1/8F++++R5yruRh4cKF+Prrr7Fz505MmDABTz31FFbu3Ant2bMAgBEjRmD1smVIUblAFEUcPnwYq1evhk6nQ25uriUO2W4ZDCK+PpyO6P/uwVfx6Xi0bzB2zB2EwaHelg6tSSll1jeHYIOSmlmzZmH06NEYOnSo2QK5U5sJCQnQ6XS11oWGhiIoKAgHDhy4ZXtarRaFhYW1HnQdKzVETSskJASJiYk4ePAgnnzySUyePBknT540rc+9eB4/vPc2jl3OwdwXYzFt5ZfQt+sFw7HfsPbpaUB+OTJzitG5czjmz5+PF154Ae+tW4fKnByUp6Tg+QcewIghQ9A/KgpyuRxjx47F5MmTAQASCfvJNZfzuSV4cMUBvPDNcfRv54md8+7FiyND0aoFDaLXUNZYqal3R+GNGzfiyJEjiI+PN1sQd2szKysLDg4OcHV1rbXcx8cHWVlZt9xn8eLFWLBggdlitDWOpkoNkxqipuDg4ID27dsDAHr27In4+Hi8//77WLFiBQDg2M7tOJmTB51ejylTp8JVo0LsG6/g/MVMfLvha1ScPIILG/+HxVs2wa9vFCK6dsOlS5cg694dRz5ci/MuPlj71ddYra9EdnY2/Pz8sHLlSqhUKnh5eVny0O1CuU6Pn45nYsGWZHg4O+DL6f0Q2c7D0mE1K2u8pbteSU16ejrmzJmDnTt3Qqk0z3DfTdEmAMTGxmLevHmm14WFhQgMDDRb+y2dUm78JcdKDVHzMBgM0Gq1AIBKnQ4nf9+N41eu4f7776+VhLQO8sNzL84BAPzy65849OlyFP22EZtS0uHo6IQ3Zs/FXocIXFA54IfVcegW6IbRXfwQIJVi48aNuO+++1ipaUI6vQE/JGbg/V9PI/1aGWI6++LtByNs4hbt+mrxt3QnJCQgJycHPXr0MC3T6/XYt28fPvzwQ2i1Wkil9evdXZc2fX19UVFRgfz8/FrVmuzsbPj6+t6yXYVCAYVCUa9Y7Ilj1S3dvPuJyPxiY2MxcuRIBAUFoaioCBs2bMCePXuwY8cOAMDvGz5FRk4OjqecwZKl79+0/5YtW5CdnY1+/frhkddew9p1X2Dv5h2I6tgGmsKLeGR4FIpVTlj+zQ/43bUtvt5aicDLu3HixAmsW7euuQ/XLhSU6fD7mStYuvM00q6UYGiYDz6Z3BsdfFSWDs1irHG6nXolNdHR0UhKSqq1bOrUqQgNDcX8+fPrndDUtc2ePXtCLpfj119/xYQJEwAAKSkpuHjx4k13E1Dd1BynhojMKycnB0888QQyMzOh0WgQERGBHTt2YNiwYQCAzDMpOHQuHR5qNbq0Cb5pf7lcjo8++ghz586FKIpo3749np85HW7ZF9D7/gcx8NEHcerUKWxYvAOX/jqFLEiQGtwVr3z0NYKCbm6PGkYURRy5mIfVv5/DthPGrg59WrvjfxN7oJO/2sLRWZ5C1sKnSVCpVAgPD6+1zNnZGR4eHqblWVlZyMrKQmpqKgDjHQAqlQpBQUFwdzdO2BUdHY1x48Zh9uzZdWpTo9Fg2rRpmDdvHtzd3aFWq/H0008jMjKy3ndZkZGiasA9aysdEtmCNWvW3HH9Q68tRud7o3Hw+2+x8d//QqvQCAye/Hf4tDX2wYmJiak16F5u+gV89sIz6BpzPwZNMnYGDgsLw9GjRwEYx0VZvO0UPj54EQkFcXhrQgRaezrf/MZUZ8kZBXjth2QcvpCHNp7OeG1MJwwJ9UawB89rNYVMYnX9Ms0+ovDy5ctrddAdNGgQAOPImFOmTAEApKWl1fuWw6VLl0IikWDChAnQarUYMWIEPv74Y7PFbW8EQYBSLuGklkQWIJPL0XXYSHSJHo4zBw/gjy+/wPqX5qHPAw8h8m+PQCqr/U/zb5+ugdrTB/c+NvWW7amUcrw5rgvu6+KH+ZuPI+b9fXh+eAimDmjTYidLbG55JRX47uhlHE3Px6FzV5FdqEWAmyPWTO6FwSHekPA83qR6QktrmkNQEEXRLib/KSwshEajQUFBAdRqlg0BoPvCXzB9UFs8FdXe0qEQ2TWDXo8Dm7/CwW83wiOgNe6b+y94tLp+Y8OaObMQFN4Zw6Y/dde2Sisq8c6OFHy6/zy6Bbri7QkRdt3v424yC8rw2YEL+PzABVToDYhopUGPYDd0C3TF0DAfTiNzB98mXMJzm47h9KKRTXqe6vP9zbmf7JhSLkU5KzVEFieRSjHgwUfRrnsvbHnvP/jshWdw72N/R/eY+yAIAgx6HWTyuv1z7eQgw2tjOmN0Fz+88M1xjP7gD9Os0NV96choW1Im/vXNcegNIh6PDMY/B7WFhwtvMKkrRdVdtOWV1jOHIJMaO+Yol6Lcyjp5Edkz3/YdMeXdD7Dns7XY/ekKnEs8ilGzn4UgkUJfWVmvtnq1dsfWOQPxwa9nsGJfGj7cnYq2ns7YOmeg3SY3JzMK8eHuM/DTOOLguas4cbkQo7r4YvH4CGgc7e+W7MaqHsRVqzMA5huRpVGsI7Uii1DIpexTQ2Rl5Aolhk1/EmP/9SoyUpKx8qm/oyTvCgpy6j/1gVIuxQsxodjy9D0IcnfC2dwSRL+7F5sOp0NvsIueBya7U3Iw7uM/cSy9AD8ey0CwuzNWPN4TH07swYSmgaorNdZ0WzcrNXbMUW59PdeJyKh9r774+3vLcXzXdlz66xTadOtx951uI9RXjX0vDEZqThHe/eU0/vXNcSzfm4Yno9rj/q7+VnPpwNyuFGnxnx0pSLiYh9ScYkSHeuOjST3stlJlbgqZ9c0hyKTGjinlUo5TQ2TFnF3dEPm3iWZrr723Csse64njl/Lx3q4zeH7TMby9/RTCW2nwTHQHdAt0Ndt7WZLBIGLL8Qws3HISV0sqMLFPEJ4e0h73RfjzbjAzUrJSQ9bEUW59Q1wTUdOLCHDFJ1N6IzWnCKt/P4eN8en47VQOHukdiEl9g9ElQGPpEBtEFEXEnb2Gxdv+wvFLBYgO9cYz0R3Q1UaSNWtTXamxpgH4mNTYMaVcioIynaXDICILae+twpIJEXjlvk74Iu4CPv3zPDbGp6OzvxoP9QpETLgvfNRW0gP0NgwGEYmX8rHjRBa2J2fhwtVSRARosHFGP/Rra18TTDa364O4slJDVkAplyK7sNzSYRCRhbkoZJh5bzv845422Hv6CjbGp2PhTyfx2o/JmHZPG0zp3xqB7k6WDtNEpzfg0Llr2H4iC7+czEJ2oRYezg4Y1skHC8eGY2B7Tw6W1wyq+yaxUkNWQSmXsE8NEZnIpBJEh/kgOswHBaU6LN72Fz47cB5r/jiH8d1bYUxXfxRpK9HawwkdfVTN2uG2XKfH72dysf1EFnb9lY2CMh1auTpidBd/jOjsg16t3dlfpplVV2q0VtSNgUmNHTP2qWFSQ0Q30zjJsWRCBF4eHYbvj17G/35Lxeajl03r5VIBfdq4Y3CIN6JCvNHOy9nsQ+Xnl1Zg7+kr2JGchT0pV1BaoUd7bxc83i8YIzr7IryV2mqG57dHvKWbrIqSHYWJ6C5USjkej2yNSX2DcSmvDC5KGS5cLUFiej72pFzB2ztSsOjnvxDk7oTBIV5o76OCVqeHxlEOf1dH+GmU8NM4wtHh9lWdikoDLl4rxdkrxUi7UoKzV4pxOrsISZcLYBCBiAANZg1ujxGdfdHe26UZj57uRFFz8D0rwaTGjjk6sFJDRHUjkQgI8jD2q3F3dkD3IDdMHdAGZRV6HDibi92nrmDXXzn4LO4CnORSlNwwsKdaafy6cXSQwkulgEImRUWlAZfzy3CtpMK0nYtChrZezmjv5YJH+wZhUEcv+Gkcm+9Aqc6kEgFyqcBKDVkHhYx9aoiocRwdpBgS6oMhoT5YKIqo0BugkBl/MGUVlCOjoAyZ+eXIKdJCEICyCj2uFGtRUWmAXCpgaJgP/DRKBLo7oZ2XM7xUCl5SakEUMik7CpN1qK7UWNO08UTUcgmCYLokoZRL0drTGa09nS0cFTUlpZWNTG+bY2NTnShlUhhEoEJvPVk2ERG1HNZWqWFSY8eqO+6xszARETWEQiZhUkPWoXreDmsqHRIRUcuhsLKhQZjU2LHqgbOs6QNJREQth0ImsapbupnU2LHqpIZ3QBERUUMYLz9Zz3cIkxo75ihnnxoiImo4axvElUmNHTNVaiqsJ8smIqKWg5UashqmSo0VfSCJiKjlUMh5SzdZCdPdT6zUUAu0ePFi9O7dGyqVCt7e3njggQeQkpJSa5uVK1ciKioKarVx4sP8/HzLBEtko5QyDr5HVoIdhakl27t3L2bNmoW4uDjs3LkTOp0Ow4cPR0lJiWmb0tJSxMTE4KWXXrJgpES2SyG3rnFqOE2CHVPIJBAEdhSmlmn79u21Xn/66afw9vZGQkICBg0aBAB49tlnAQB79uxp5uiI7ANHFCarIQgClDIpKzVkEwoKCgAA7u7uFo6EyH4oePmJrIm1TUZG1BAGgwHPPvssBgwYgPDwcEuHQ2Q3lFbWUZiXn+yco5UNcU3UELNmzcKJEyfwxx9/WDoUIrtiHFHYer5DmNTYOSWTGmrhZs+ejZ9++gn79u1DQECApcMhsisKmQTlVlSp4eUnO6eUs08NtUyiKGL27Nn47rvv8Ntvv6FNmzaWDonI7ijlUlRUGiCKoqVDAcBKjd0z9qmxniybqK5mzZqFDRs24IcffoBKpUJWVhYAQKPRwNHREQCQlZWFrKwspKamAgCSkpKgUqkQFBTEDsVEZqCoGu9MW2kwDRNiSazU2DlHB1ZqqGVatmwZCgoKEBUVBT8/P9Pjq6++Mm2zfPlydO/eHdOnTwcADBo0CN27d8ePP/5oqbCJbIpCZkxkrKWzMCs1dk4pk1pVJy+iuqpLufv111/H66+/3vTBENmp6pHptTo94Ci3cDSs1Ng9JSs1RETUQNZWqWFSY+eUMuuaNp6IiFoOhay6T411/DhmUmPnHB0kKOOElkRE1ADVnYOt5ccxkxo7p5RJUW4lGTYREbUsrNSQVXF0kKKclRoiImoAU58aW6jULFmyBIIgmGbCBYCVK1ciKioKarUagiAgPz//ru0sW7YMERERUKvVUKvViIyMxLZt22ptExUVBUEQaj1mzpzZmPAJVSMKW0kHLyIialmq736ylop/g5Oa+Ph4rFixAhEREbWWl5aWIiYmBi+99FKd2woICMCSJUuQkJCAw4cPY8iQIRg7diySk5NrbTd9+nRkZmaaHm+//XZDw6cqSrmUfWqIiKhBrK1S06BxaoqLizFp0iSsWrUKixYtqrWuumqzZ8+eOrc3ZsyYWq/feOMNLFu2DHFxcejcubNpuZOTE3x9fRsSMt2GUi5BeaUeoihCEARLh0NERC1IzRGFrUGDKjWzZs3C6NGjMXToUHPHA71ej40bN6KkpASRkZG11q1fvx6enp4IDw9HbGwsSktLb9uOVqtFYWFhrQfdzFEuhShazweSiIhajuqOwtYyMXK9KzUbN27EkSNHEB8fb9ZAkpKSEBkZifLycri4uOC7775Dp06dTOsfffRRBAcHw9/fH8ePH8f8+fORkpKCzZs337K9xYsXY8GCBWaN0RZV346n1VnHvB1ERNRyCIIAB5nEan4Y1yupSU9Px5w5c7Bz504olUqzBhISEoLExEQUFBTgm2++weTJk7F3715TYjNjxgzTtl26dIGfnx+io6ORlpaGdu3a3dRebGws5s2bZ3pdWFiIwMBAs8ZsCxyrEpkynR4aWH6IayIialkUMonV3NJdr6QmISEBOTk56NGjh2mZXq/Hvn378OGHH0Kr1UIqbdivfQcHB7Rv3x4A0LNnT8THx+P999/HihUrbrl93759AQCpqam3TGoUCgUUCkWDYrEn1ddDraV0SERELYtSbj0j09crqYmOjkZSUlKtZVOnTkVoaCjmz5/f4ITmVgwGA7Ra7W3XJyYmAgD8/PzM9p72qGalhoiIqL5abKVGpVIhPDy81jJnZ2d4eHiYlmdlZSErKwupqakAjH1lVCoVgoKC4O7uDsCYHI0bNw6zZ88GYLxUNHLkSAQFBaGoqAgbNmzAnj17sGPHDgBAWloaNmzYgFGjRsHDwwPHjx/H3LlzMWjQoJtuKaf6uT7EtXV8IImIqGVRyCQt+5buO1m+fHmtDrqDBg0CAKxduxZTpkwBYExScnNzTdvk5OTgiSeeQGZmJjQaDSIiIrBjxw4MGzYMgPHS1K5du/Dee++hpKQEgYGBmDBhAl555RVzh293WKkhIqLGMA7iah3fIYIoiqKlg2gOhYWF0Gg0KCgogFqttnQ4ViOroBz9Fv+KtVN6Y3Cot6XDISKiFmb8x3+inZcL3nmwa5O0X5/vb879ZOdYqSEiosZQyKRWc0s3kxo7x7ufiIioMZRy6+kozKTGzilkEggCKzVERNQwCpn13NLNpMbOCYIApRV9IImIqGVRsFJD1sTRQcrLT0RE1CBK9qkha6KUSZjUEBFRgyjkEqup9jOpISgdpCirYFJDRET1Z00jCjOpIWOfGiv5QBIRUcuilEutZkRhJjUERwcpyiqs4wNJREQtCys1ZFWUcgkKynSWDoOIiFoghcx6KjVmn/uJWp6KSgOK7zAjOhER0e0Yb+m2jqSGlRqCh7MCShk/CkREVH9KmRQVegP0BstPJclvMoLGUW41WTYREbUs1dPtVFjB9wiTGrKq0iEREbUsiqpKvzV0FmZSQ1bVc52IiFoWhVwKAFYxAB+TGrKqMQaIiKhlYaWGrAorNURE1FAKmbFSYw3dGJjUkFVNG09ERC2LsqqjsDXMIcikhqC0omnjiYioZWGlhqyKQiaFTi9axRgDRETUspj61FhBxZ9JDZnGGGC1hoiI6ktpuvvJ8t8hTGroeunQCrJsIiJqWa7/MLb8dwiTGjJ9IMtZqSEionriLd1kVZSs1BARUQM5SCUQBFZqyEpYU+mQiIhaFkEQoJBJ2KeGrEN16dAaPpBERNTyKGRSq/hhzKSGTD3XreEDSURELY9SLrGKLgxMaoiVGiIiahSFTGoVN5swqSGrGg2SiIhaHoWMlRqyEtY0bwcREbU8SrmUt3STdWClhoiIGsN495Plv0OY1BDkUgESgZUaIiJqGIWVTIzMpIYgCAKUcimTGiIiahClTMpKDVkP4/VQy38giYio5WGfGrIq1jIaJBERtTwKuXV8hzCpIQCs1BARUcM5yqUoY1JD1oKVGiIiaiilXIqyCst/hzCpIQBgR2EiImowR7kNdBResmQJBEHAs88+a1q2cuVKREVFQa1WQxAE5Ofn37WdZcuWISIiAmq1Gmq1GpGRkdi2bVutbcrLyzFr1ix4eHjAxcUFEyZMQHZ2dmPCpxqUcusYY4CIiFoeZUvvUxMfH48VK1YgIiKi1vLS0lLExMTgpZdeqnNbAQEBWLJkCRISEnD48GEMGTIEY8eORXJysmmbuXPnYsuWLdi0aRP27t2LjIwMjB8/vqHh0w2MM6xa/gNJREQtj7VU+2UN2am4uBiTJk3CqlWrsGjRolrrqqs2e/bsqXN7Y8aMqfX6jTfewLJlyxAXF4fOnTujoKAAa9aswYYNGzBkyBAAwNq1axEWFoa4uDj069evIYdBNbBSQ0REDaWs6igsiiIEQbBYHA2q1MyaNQujR4/G0KFDzR0P9Ho9Nm7ciJKSEkRGRgIAEhISoNPpar1faGgogoKCcODAAbPHYI+sJcsmIqKWx1EuhUEEKvSW/XFc70rNxo0bceTIEcTHx5s1kKSkJERGRqK8vBwuLi747rvv0KlTJwBAVlYWHBwc4OrqWmsfHx8fZGVl3bI9rVYLrVZrel1YWGjWeG2NUiZFOW/pJiKiBlBUTYysrTSY5hO0hHpVatLT0zFnzhysX78eSqXSrIGEhIQgMTERBw8exJNPPonJkyfj5MmTDW5v8eLF0Gg0pkdgYKAZo7U9SrkEWlZqiIioAWQS4yUnvV60aBz1SmoSEhKQk5ODHj16QCaTQSaTYe/evfjggw8gk8mg1zf8S9HBwQHt27dHz549sXjxYnTt2hXvv/8+AMDX1xcVFRU33UmVnZ0NX1/fW7YXGxuLgoIC0yM9Pb3BsdkDBQffIyKiBpJU9aPRi5ZNaup1+Sk6OhpJSUm1lk2dOhWhoaGYP38+pFLzlZwMBoPp8lHPnj0hl8vx66+/YsKECQCAlJQUXLx40dTv5kYKhQIKhcJs8dg6JQffIyKiBpJJjUmNwdCCkhqVSoXw8PBay5ydneHh4WFanpWVhaysLKSmpgIw9pVRqVQICgqCu7s7AGNyNG7cOMyePRuAsaoycuRIBAUFoaioCBs2bMCePXuwY8cOAIBGo8G0adMwb948uLu7Q61W4+mnn0ZkZCTvfDITBTsKExFRA1VXaipbUlJTF8uXL8eCBQtMrwcNGgTAeAv2lClTAABpaWnIzc01bZOTk4MnnngCmZmZ0Gg0iIiIwI4dOzBs2DDTNkuXLoVEIsGECROg1WoxYsQIfPzxx+YO324prWQ0SCIianmk1X1qLJzUCKJo4QtgzaSwsBAajQYFBQVQq9WWDsfqfBF3Af/+4QTS3hxl0TEGiIio5TmQdhUTV8Xht+fuRVsvF7O2XZ/vb879RACMlRqDCOgs3HOdiIhaHmeFsU9tqYUntWRSQwCMt3QDQDmnSiAionpyVhh7s1g6qTF7nxpqmZRVgyUdOnsNvholHB2kUMqlcJBK4CCTQCGTwEEqgUTCS1NERFSbs4MxnSjRVlo0DiY1BADwURsHU/zHZ4fvuJ1MIkBeleg4VCU6Clnt17d6rpBJjPvVXH+L/W/cxrRfzfZueA+ZlAVHIiJLUppGFGalhqxAlwAN4l8eioIyHcoq9CjT6VGu06Oi0oAKvcH4Z6UB2hrPjev0NZ4boK21zoBibWXtNvS111c/b8xtgBIBpsSnuqIkvyH5kUuvr6uVQNVIrG5M1uRSATKpBFKJALlUgFQigVwiQCoRIJMKkEkkkElu3KZquVQwrZNV7SOXSCCtXl61jJ2yicgWVE+NYOlBXJnUkImXSgEvlWUGLNQbROj0NyQ9t0mGdPqbkyjdjcnSDe3UbLtYW4mKEsNN76fTi1Xt6VGhN6BSLzb5mAumhOc2iZEpGbrduhuSruqESSaVwKEqKZPf8FwuFar+NLbjcJvn1VUzmWn76/vd+JzJGZF9c5BVVWosPDQIkxqyClKJAKnE2I/HmoiiCL3BmNxUGkTo9SJ0BsP1ZXpD1Z8iKg3XEyF9zXVVy/UGETqDCL3BmEDV3MaY1N2w7oY2rm9z43sbUK4Ta7yH8f10emPiVmkQoas0oKIqRl2lATqDiAoz/qKqTs5kEgESiYC7pThSiVBVWZPCQWZMxvSG6/Ebz7MxoXSUS6GUS+Aol0Ihl9Z67egghUImhSjWOO8GEQaDWGu4dgEwJV5CzYUABAgQhFqLIAjG5bcikQiQSgCpYDzW6j8lwp2XSwShVsJYnRjKJDWeVyWWshuTT8n1fWQ1kk0Zq31kJap/XPHyE5EVE4SqS03WlWuZRc2ErboyVV3xqjRcT4p0+trPK/XVVa7az/V6A/QioDfcOVkSReOoozUrcJV6Q61LddXPAaBcd/1yaLnOYLo8ml+qMy0TBFRVrySQCoBMIjEmJoLx/QDAlOKYXoumeGquF0URt6vPiSJgqDpveoNoei6Kxjlv9DUSKr2h6hzXWF59Xs1ZALyeHAlVCWLN5Kg6Waqq1kmMl2blkpsTLFOyJBFu2KZ20nVjQuYgq2r3ltvVjKu6XYmp6siEzLYoZJafQ5BJDZGdqpmwWVuFzNZVX26trqLpDLUTRuPz6mSzKrGsqrJdTzir2qiRYFYni5WG2sno9bau71um06NSW7Odm5PXG6t7Or0B5hyu9VYJmVwmVCU+NyRdt0jIHG5IoKqTs1slZLfe53pCVp0AixBR9Z/ptWh6XZXw1lx+wzqxagPxTm3cYX/ctH3t16jxPjXfs7oN1NjHINbeH7Xe/y5t3yIG1Hif6rYNVQ0bRNHUJcCSmNQQETWz6sutAIAWNu+u3lA7WdLpqxKeqmSqorIqEdLfKmESq7a5c3JWc1tdpXhT0lem00NXXiNZq7FdzffS1UgKK/QtcxoY46VQ448QATUujZqWX7+EWnM71Hxd47mkaqVwh/1N73uHtiVVzyXC9cu3Hbxd0DXAtflOzi0wqSEiojqz1v5vd3O7y63VCZAoijclDqa+VsLNSUX1Fz1ueC0xJRFVicdtkpJabd8icah+T6ofJjVERGTzeLnVPnDUMiIiIrIJTGqIiIjIJjCpISIiIpvApIaIiIhsApMaIiIisglMaoiIiMgmMKkhIiIim8CkhoiIiGwCkxoiIiKyCUxqiIiIyCYwqSEiIiKbwKSGiIiIbAKTGiIiIrIJdjNLtyiKAIDCwkILR0JERER1Vf29Xf09fid2k9QUFRUBAAIDAy0cCREREdVXUVERNBrNHbcRxLqkPjbAYDAgIyMDKpUKgiA0yXsUFhYiMDAQ6enpUKvVTfIeto7nsHF4/hqP57BxeP4ah+fvZqIooqioCP7+/pBI7txrxm4qNRKJBAEBAc3yXmq1mh/GRuI5bByev8bjOWwcnr/G4fmr7W4VmmrsKExEREQ2gUkNERER2QQmNWakUCjw2muvQaFQWDqUFovnsHF4/hqP57BxeP4ah+evceymozARERHZNlZqiIiIyCYwqSEiIiKbwKSGiIiIbAKTGiIiIrIJTGrq6fTp0xg7diw8PT2hVqtxzz33YPfu3ab1x44dw8SJExEYGAhHR0eEhYXh/fffv2u7R44cwbBhw+Dq6goPDw/MmDEDxcXFTXkoFtFU5+9u7dqKpjh/e/bsgSAIt3zEx8c39SE1u6b6DALAzz//jL59+8LR0RFubm544IEHmugoLKepzl/r1q1v+vwtWbKkKQ/FYpryMwgAWq0W3bp1gyAISExMbIIjsF5MaurpvvvuQ2VlJX777TckJCSga9euuO+++5CVlQUASEhIgLe3N7744gskJyfj5ZdfRmxsLD788MPbtpmRkYGhQ4eiffv2OHjwILZv347k5GRMmTKlmY6q+TTF+atLu7aiKc5f//79kZmZWevxj3/8A23atEGvXr2a69CaTVN9Br/99ls8/vjjmDp1Ko4dO4Y///wTjz76aHMcUrNqqvMHAAsXLqz1OXz66aeb+nAsoinPIQC88MIL8Pf3b8pDsF4i1dmVK1dEAOK+fftMywoLC0UA4s6dO2+731NPPSUOHjz4tutXrFghent7i3q93rTs+PHjIgDxzJkz5gneCjTV+Wtouy1NU52/G1VUVIheXl7iwoULGxWvNWqqc6jT6cRWrVqJq1evNmu81qYpP4PBwcHi0qVLzRWq1Wrq/4+3bt0qhoaGisnJySIA8ejRo+YIu8VgpaYePDw8EBISgs8++wwlJSWorKzEihUr4O3tjZ49e952v4KCAri7u992vVarhYODQ62JuhwdHQEAf/zxh/kOwMKa6vw1tN2WpqnO341+/PFHXL16FVOnTjVH2Falqc7hkSNHcPnyZUgkEnTv3h1+fn4YOXIkTpw40RSHYTFN/RlcsmQJPDw80L17d7zzzjuorKw0Z/hWoSnPYXZ2NqZPn47PP/8cTk5O5g69ZbB0VtXSpKeniz179hQFQRClUqno5+cnHjly5Lbb//nnn6JMJhN37Nhx221OnDghymQy8e233xa1Wq147do1ccKECSIA8c0332yKw7CYpjh/DWm3pWqq81fTyJEjxZEjR5ojXKvUFOfwyy+/FAGIQUFB4jfffCMePnxYnDhxoujh4SFevXq1KQ7DYprqM/juu++Ku3fvFo8dOyYuW7ZMdHV1FefOnWvu8K1CU5xDg8EgxsTEiP/3f/8niqIonjt3zi4rNUxqRFGcP3++COCOj7/++ks0GAzi/fffL44cOVL8448/xISEBPHJJ58UW7VqJWZkZNzUblJSkujp6Wn6kN3J+vXrRR8fH1EqlYoODg7i888/L/r4+IhLlixpikM2K0ufv/q2a20sff5qSk9PFyUSifjNN9+Y8xCbnKXP4fr160UA4ooVK0zLysvLRU9PT3H58uVmP15zs/T5u5U1a9aIMplMLC8vN8chNjlLn8P3339fHDBggFhZWSmKIpMau5aTkyP+9ddfd3xotVpx165dokQiEQsKCmrt3759e3Hx4sW1liUnJ4ve3t7iSy+9VK9YsrKyxKKiIrG4uFiUSCTi119/3ejja2qWPn/1adcaWfr81bRw4ULRy8tLrKioaPRxNSdLn8PffvtNBCD+/vvvtZb36dOn3n8HlmDp83crJ06cEAGIp06davBxNSdLn8OxY8eKEolElEqlpgcAUSqVik888YRZj9Waycx3Iavl8vLygpeX1123Ky0tBYBafV+qXxsMBtPr5ORkDBkyBJMnT8Ybb7xRr1h8fHwAAJ988gmUSiWGDRtWr/0twdLnr67tWitLn79qoihi7dq1eOKJJyCXy+u8nzWw9Dns2bMnFAoFUlJScM899wAAdDodzp8/j+Dg4PocikVY+vzdSmJiIiQSCby9vRu0f3Oz9Dn84IMPsGjRItPrjIwMjBgxAl999RX69u1b18No+SydVbUkV65cET08PMTx48eLiYmJYkpKivj888+LcrlcTExMFEXRWCr08vISH3vsMTEzM9P0yMnJMbVz8OBBMSQkRLx06ZJp2f/+9z8xISFBTElJET/88EPR0dFRfP/995v9GJtSU52/urRrC5ry8yeKxooXqkrktqopz+GcOXPEVq1aiTt27BBPnTolTps2TfT29havXbvW7MfZVJrq/O3fv19cunSpmJiYKKalpYlffPGF6OXlZZMVhqb+/7gaLz9RncTHx4vDhw8X3d3dRZVKJfbr10/cunWraf1rr712y2upwcHBpm12794tAhDPnTtnWvb444+L7u7uooODgxgRESF+9tlnzXhUzaepzt/d2rUVTXX+RFEUJ06cKPbv37+ZjsRymuocVlRUiM8995zo7e0tqlQqcejQoeKJEyea8ciaR1Ocv4SEBLFv376iRqMRlUqlGBYWJr755pstpj9NfTXl/8fV7DWpEURRFJuwEERERETULDhODREREdkEJjVERERkE5jUEBERkU1gUkNEREQ2gUkNERER2QQmNURERGQTmNQQERGRTWBSQ0RERDaBSQ0RERHZBCY1REREZBOY1BAREZFNYFJDRERENuH/AQuhYD2r6JtRAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unit 3068 has island pieces.  We will reduce the tract to its main state component\n",
      "unit 3097 has island pieces.  We will reduce the tract to its main state component\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unit 1006 is a true island.  We will move it to adjoin the mainland in same county.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#RUN THIS ONLY IF WE FOUND POPULATED ISLANDS\n",
    "nSubGeoms = len(MAP.geoms)\n",
    "subGeoms = [MAP.geoms[n] for n in range(nSubGeoms)]\n",
    "subAreas = [subGeoms[n].area for n in range(nSubGeoms)]\n",
    "mainSubGeomNo = subAreas.index(np.max(subAreas))\n",
    "mainGeom = subGeoms[mainSubGeomNo]\n",
    "nonMainGeom = dummyPoly\n",
    "for geo in subGeoms:  #the \"nonMainGeom is all pieces of the state not in the biggest piece\n",
    "    if geo != mainGeom:\n",
    "        if nonMainGeom == dummyPoly:\n",
    "            nonMainGeom = geo\n",
    "        else:\n",
    "            nonMainGeom = nonMainGeom.union(geo)\n",
    "        \n",
    "print(\"Lets first identify which county each island belongs to.  Then we'll move the island to the closest county mainland\")\n",
    "hasIsland, isIsland = [False for c in range(nCounties)], [False for c in range(nCounties)]\n",
    "isIsland =  [False for t in range(nTracts)]\n",
    "islandXshift, islandYshift = [0. for t in range(nTracts)], [0. for t in range(nTracts)]\n",
    "islandList = list()\n",
    "for c in range(nCounties):\n",
    "    if countyGeom[c].intersects(nonMainGeom):  #this county contains an island.  Find all its island tracts\n",
    "        hasIsland[c] = True\n",
    "        if countyGeom[c].disjoint(mainGeom):  #need to connect the whole county\n",
    "            print(\"county\",c,\"is completely disconnected from mainland.  Move it to adjoin mainland\")\n",
    "            isIsland[c] = True\n",
    "            countyDist = [999999. for cc in range(nCounties)]  #default, to avoid picking island counties as closest to this one\n",
    "            for cc in range(nCounties):\n",
    "                if countyGeom[cc].intersects(mainGeom):\n",
    "                    countyDist[cc] = countyGeom[c].distance(countyGeom[cc].intersection(mainGeom) )\n",
    "            closestCounty = countyDist.index(np.min(countyDist))\n",
    "            p1, p2 = nearest_points(countyGeom[closestCounty],countyGeom[c])\n",
    "            for t in countyTractList[c]:\n",
    "                islandXshift[t], islandYshift[t]  = p1.x - p2.x , p1.y - p2.y\n",
    "            for t in countyTractList[c]:\n",
    "                plotPoly(tractGeom[t])\n",
    "                plotCenter(t,tractGeom[t])\n",
    "                plt.arrow(tractCP[t].x, tractCP[t].y,islandXshift[t], islandYshift[t])\n",
    "                tractGeom[t] = translate(tractGeom[t], xoff=islandXshift[t], yoff=islandYshift[t])                   \n",
    "                tractCP[t] = tractGeom[t].centroid\n",
    "                tractCPx[t], tractCPy[t] = tractCP[t].x, tractCP[t].y\n",
    "                plotPoly(tractGeom[t],0.2)\n",
    "        else: #move only the county's island tracts to connect with main geom\n",
    "            mainCountyGeom = countyGeom[c].intersection(mainGeom)\n",
    "            plotPoly(mainCountyGeom)\n",
    "            plotCenter(c,mainCountyGeom)\n",
    "            for t in countyTractList[c]:\n",
    "                if tractGeom[t].intersects(nonMainGeom) and t not in skipList:\n",
    "                    if tractGeom[t].intersects(mainCountyGeom):\n",
    "                        print(\"unit\",t,\"has island pieces.  We will reduce the tract to its main state component\")\n",
    "                        plotPoly(tractGeom[t],0.2)\n",
    "                        tractGeom[t] = tractGeom[t].intersection(mainCountyGeom)\n",
    "                        tractCP[t] = tractGeom[t].centroid\n",
    "                        tractCPx[t], tractCPy[t] = tractCP[t].x, tractCP[t].y\n",
    "                        plotPoly(tractGeom[t])\n",
    "                        plotCenter(t,tractGeom[t])\n",
    "                    else:    \n",
    "                        isIsland[t] = True\n",
    "                        print(\"unit\",t,\"is a true island.  We will move it to adjoin the mainland in same county.\")\n",
    "                        islandList.append(t)\n",
    "                        if tractGeom[t].geom_type != dummyPoly.geom_type :  #island tract is multiple geoms.  collapse to its largest isle\n",
    "                            isleGeos = [geo for geo in tractGeom[t].geoms]\n",
    "                            isleAreas = [geo.area for geo in isleGeos]\n",
    "                            biggestIsleNo = isleAreas.index(np.max(isleAreas))\n",
    "                            tractGeom[t] = isleGeos[biggestIsleNo]\n",
    "                            tractCP[t] = tractGeom[t].centroid\n",
    "                        p1, p2 = nearest_points(mainCountyGeom, tractGeom[t])\n",
    "                        islandXshift[t], islandYshift[t]  = p1.x - p2.x , p1.y - p2.y\n",
    "                        plotPoly(tractGeom[t])\n",
    "                        plotCenter(t,tractGeom[t])\n",
    "                        plt.arrow(tractCP[t].x, tractCP[t].y,islandXshift[t], islandYshift[t])\n",
    "                        tractGeom[t] = translate(tractGeom[t], xoff=islandXshift[t], yoff=islandYshift[t])                   \n",
    "                        tractCP[t] = tractGeom[t].centroid\n",
    "                        tractCPx[t], tractCPy[t] = tractCP[t].x, tractCP[t].y\n",
    "                        plotPoly(tractGeom[t],0.2)\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9a94118d-5863-4458-b77a-67d18cf01c2c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If you like my proposed translations, let's rebuild the MAP with the adjusted county geoms\n",
      "This would need adjustment for multi-county islands like Michigan UP\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing with island triage - RUN ONLY WITH ISLANDS\n",
    "print(\"If you like my proposed translations, let's rebuild the MAP with the adjusted county geoms\")\n",
    "print(\"This would need adjustment for multi-county islands like Michigan UP\")\n",
    "for c in range(nCounties):\n",
    "    if hasIsland[c] :  #rebuild the county geom with the translated islands\n",
    "        countyGeom[c] = dummyPoly\n",
    "        for t in countyTractList[c]:\n",
    "            if t not in skipList:\n",
    "                if countyGeom[c] == dummyPoly:\n",
    "                    countyGeom[c] = tractGeom[t]\n",
    "                else:\n",
    "                    countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "MAP = countyGeom[0]\n",
    "plotPoly(countyGeom[0])\n",
    "for c in range(1,nCounties):\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "    plotPoly(countyGeom[c])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4aebe4ee-ee7b-4bf3-8413-f315556d453e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "computing all county centerpoints, then plot them\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"computing all county centerpoints, then plot them\")\n",
    "countyCP  = list()\n",
    "cutCountyList = list()\n",
    "for c in range(nCounties):\n",
    "    cTL = countyTractList[c]\n",
    "    countyCP.append(getHDcp( [tractCP[v] for v in cTL], [tractPop[v] for v in cTL], [i for i in range(len(cTL) ) ] ) )\n",
    "    if countyCP[c].disjoint(countyGeom[c]):  #possible with weird-shaped county\n",
    "        countyCP[c] = nearest_points(countyGeom[c],countyCP[c])[0]\n",
    "    plotPoly(countyCP[c].buffer(0.03))\n",
    "    plotPoly(countyGeom[c],0.5)\n",
    "plotPoly(MAP)\n",
    "plt.show()   \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "207f3a55-e361-4777-ae46-41fe3d54a4b8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This code block reads in a csv with whole districts to be cut out of the map\n",
      "For IL my input file says to cut out 0 districts out of 17\n",
      "There were no cut districts in IL\n"
     ]
    }
   ],
   "source": [
    "print(\"This code block reads in a csv with whole districts to be cut out of the map\")\n",
    "unclippedMAP = MAP\n",
    "trimDF = pd.read_csv(\"state_map_files/cutNclipPolyLists.csv\")\n",
    "stateRows = trimDF[\"state\"].to_list()\n",
    "DFrow = stateRows.index(STATE)\n",
    "nClips = trimDF[\"nClipPoly\"][DFrow]\n",
    "nCuts  = trimDF[\"nCutPoly\"][DFrow]\n",
    "nCutDistricts = nCuts\n",
    "nStops = trimDF[\"nStopLines\"][DFrow]\n",
    "nDistricts = trimDF[\"nDistricts\"][DFrow]\n",
    "stopLines = list()  #the 'stoplines' stop wedge growth that hops across concave map areas (not currently used)\n",
    "cutCountyList = list()\n",
    "allCutLists, allCutPops = list(), list()\n",
    "print(\"For\",STATE,\"my input file says to cut out\",nCuts,\"districts out of\",nDistricts)\n",
    "if nCuts > 0:\n",
    "    cutList = list()\n",
    "    cutXs = ast.literal_eval(trimDF[\"cutXs\"][DFrow])\n",
    "    cutYs = ast.literal_eval(trimDF[\"cutYs\"][DFrow])\n",
    "    cutPoints = [Point(cutXs[i],cutYs[i]) for i in range(len(cutXs)) ]\n",
    "    for cutNo in range(nCuts):\n",
    "        print(\"performing cut no\",cutNo,\"for state\",STATE)  #first two cutPoints must form the cutLine\n",
    "        cutNotDone = True\n",
    "        thisCutPoints = [ cutPoints[int(4*cutNo)],cutPoints[int(4*cutNo+1)],cutPoints[int(4*cutNo+2)],cutPoints[int(4*cutNo+3)]  ]\n",
    "        while cutNotDone:\n",
    "            cutPoly = Polygon([thisCutPoints[0],thisCutPoints[1],thisCutPoints[2],thisCutPoints[3] ])\n",
    "            cutLine = LineString([thisCutPoints[0], thisCutPoints[1] ] )\n",
    "            cutList = list()\n",
    "            cutPop = 0.\n",
    "            for c in range(nCounties):\n",
    "                if cutPoly.intersects(countyGeom[c]):\n",
    "                    if cutPoly.contains(countyGeom[c]):\n",
    "                        cutList = cutList + countyTractList[c]\n",
    "                        cutPop += countyPop[c]\n",
    "                    else:\n",
    "                        for t in countyTractList[c]:\n",
    "                            if cutPoly.contains(tractCP[t]):\n",
    "                                cutList.append(t)\n",
    "                                cutPop += tractPop[t]\n",
    "                            if STATE == \"NC\":\n",
    "                                if t == 1828:\n",
    "                                    print(\"special for NC - include vtd 1828 from county 55 in the cut list for contiguity\")\n",
    "                                    cutList.append(t)\n",
    "                                    cutPop += tractPop[t]\n",
    "            print(\"the total proposed cutPop is\",cutPop,\". Compare to\",int(statePop/nDistricts) )\n",
    "\n",
    "            doIcut = input(\"enter 1 to apply the cut\")\n",
    "            if str(doIcut) == str(1):\n",
    "                cutNotDone = False\n",
    "                allCutLists.append(cutList)\n",
    "                allCutPops.append(cutPop)\n",
    "            else:\n",
    "                print(\"Here is the state and the last proposed cutPoly.\")\n",
    "                plotPoly(cutPoly)\n",
    "                plotPoly(MAP)\n",
    "                plt.show()\n",
    "                print(cutPoly)\n",
    "                oldPts = list(cutPoly.exterior.coords)\n",
    "                newPtXs = ast.literal_eval(input(\"enter alternate [ x0, x1 ] for the first two points\") )\n",
    "                newPtYs = ast.literal_eval(input(\"enter alternate [ y0, y1 ] for the first two points\") )\n",
    "                thisCutPoints = [Point(newPtXs[0],newPtYs[0]), Point(newPtXs[1],newPtYs[1]),oldPts[2], oldPts[3] ]\n",
    "allCutVTDs = list()\n",
    "for L in allCutLists:\n",
    "    for v in L:\n",
    "        allCutVTDs.append(v)\n",
    "if nCutDistricts == 0:\n",
    "    print(\"There were no cut districts in\",STATE)\n",
    "else:\n",
    "    print(\"here are your cut districts\")\n",
    "    plotPoly(MAP)\n",
    "    for i,L in enumerate(allCutLists):\n",
    "        cutGeo = tractGeom[L[0]]\n",
    "        for v in L:\n",
    "            cutGeo=cutGeo.union(tractGeom[v])\n",
    "        plotPoly(cutGeo,2)\n",
    "        plotCenter(i,cutGeo)\n",
    "        plotCenter(allCutPops[i],Point(cutGeo.centroid.x,cutGeo.centroid.y-0.5) )\n",
    "    plt.show()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4c915415-6c44-4c43-9826-b565cebed95a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Write the vtd cutlists to a file\n"
     ]
    }
   ],
   "source": [
    "print(\"Write the vtd cutlists to a file\")\n",
    "cutDistrictNo = list()\n",
    "for v in allCutVTDs:\n",
    "    for i,L in enumerate(allCutLists):\n",
    "        if v in L:\n",
    "            cutDistrictNo.append(i)\n",
    "            break\n",
    "nbrDF = pd.DataFrame( {\"vtdNo\":allCutVTDs,\"cutDistrictNo\":cutDistrictNo} )\n",
    "outname = STATE+\"wholeDistrictCuts.csv\" \n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "nbrDF.to_csv(outpath)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "17721728-e5c0-4787-b430-9d7d94970667",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17 districts\n"
     ]
    }
   ],
   "source": [
    "countyPop = [0. for c in range(nCounties)]\n",
    "for t in range(nTracts):\n",
    "    countyPop[countyNo[t]] += tractPop[t]\n",
    "print(nDistricts,\"districts\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f3073320-8d92-45ba-beb2-fb8c08d7170d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Removed all whole districts.  Finalize stats before squishing in outcroppings.\n",
      "Of the total statePop 12812508.0 we ignore 0.0 as it is cut out of the map\n",
      "This excluded pop comes from a total of 2 tracts\n",
      "Our final adjusted number of state districts, excluded fixed cut-out is 17 rather than original 17\n",
      "Each district will be drawn to house 753676.941 = 1/ 17 of non-cutout state pop 12812508.0 vs original= 12812508.0\n",
      "Here is a county-level modified map with each county's fraction of a district pop\n",
      "working on county 0\n",
      "working on county 20\n",
      "working on county 40\n",
      "working on county 60\n",
      "working on county 80\n",
      "working on county 100\n",
      "here is the IL map excluding cut and unpop coastal tracts\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Removed all whole districts.  Finalize stats before squishing in outcroppings.\")\n",
    "trueCountyPop = [countyPop[c] for c in range(nCounties)]\n",
    "trueCountyGeom = countyGeom.copy()\n",
    "countyPop = [0. for c in range(nCounties)]\n",
    "trueStatePop, true_nDistricts = np.sum(trueCountyPop), nDistricts\n",
    "trueCountyTractList = [list() for c in range(nCounties)]\n",
    "# minTractPop = 4.5  #already defined above\n",
    "populatedTractList = list()\n",
    "countyTractList = [list() for c in range(nCounties)]\n",
    "statePop, excludedPop = 0., 0.\n",
    "\n",
    "for t in range(nTracts):\n",
    "    trueCountyTractList[countyNo[t]].append(t)\n",
    "    if t in allCutVTDs or t in skipList:  #  or vtdPop[t] < minTractPop:  #need to keep low-pop vtds as VEST may have assigned votes to them\n",
    "        excludedPop += tractPop[t]\n",
    "    else:\n",
    "        populatedTractList.append(t)\n",
    "        countyTractList[countyNo[t]].append(t)\n",
    "        countyPop[countyNo[t]] += tractPop[t]\n",
    "        statePop += tractPop[t]\n",
    "        #tractPop[t] = max(tractPop[t],0.000001)  #avoid possible later div/zero errors for nil-vote vtds\n",
    "print(\"Of the total statePop\",statePop+excludedPop,\"we ignore\",excludedPop,\"as it is cut out of the map\") #,\n",
    "#\"or in sparsely populated areas (<\",minTractPop,\") per geom\")\n",
    "print(\"This excluded pop comes from a total of\",nTracts -len(populatedTractList),\"tracts\")\n",
    "true_nDistricts = nDistricts\n",
    "nDistricts -= nCutDistricts\n",
    "print(\"Our final adjusted number of state districts, excluded fixed cut-out is\",nDistricts,\"rather than original\",true_nDistricts)\n",
    "aDP = statePop/float(nDistricts)\n",
    "print(\"Each district will be drawn to house\",r3(aDP),\"= 1/\",nDistricts,\"of non-cutout state pop\",statePop,\"vs original=\",trueStatePop)\n",
    "print(\"Here is a county-level modified map with each county's fraction of a district pop\")\n",
    "\n",
    "vtdGeom = tractGeom.copy()\n",
    "nVTDs = len(vtdGeom)\n",
    "\n",
    "cutCountyList, uncutCountyList = list(), list()\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"working on county\",c)\n",
    "    if len(countyTractList[c]) == 0:  #no vtds added to county b/c all were in cut lists:\n",
    "        cutCountyList.append(c)\n",
    "    else:\n",
    "        uncutCountyList.append(c)\n",
    "        countyGeom[c] = tractGeom[countyTractList[c][0]]\n",
    "        for t in countyTractList[c]:\n",
    "            countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "uncutMAP = MAP\n",
    "MAP = countyGeom[uncutCountyList[0]]\n",
    "for c in uncutCountyList:\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "print(\"here is the\",STATE,\"map excluding cut and unpop coastal tracts\")\n",
    "\n",
    "for c in uncutCountyList:\n",
    "    plotPoly(countyGeom[c])\n",
    "    FONTSIZE = 8 #11  #reduce for TX\n",
    "    if countyPop[c] / statePop < 0.02:\n",
    "        FONTSIZE = 5 #7 #reduce for TX\n",
    "        plotCenter(r3(countyPop[c]/aDP),countyGeom[c], FONTSIZE)\n",
    "    else:\n",
    "        plotCenter(round(countyPop[c]/aDP,2),countyGeom[c], FONTSIZE)\n",
    "plotPoly(trueMAP,0.1)\n",
    "for c in cutCountyList:\n",
    "    plotPoly(countyGeom[c],0.2)\n",
    "    plotCenter(\"cut\",countyGeom[c],6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0062ac21-3328-4616-99ed-70c53e62b308",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now finalize the map topology before any squish operations.  Plot countyPop/aDP\n",
      "Working on county  0 distances\n",
      "Working on county  20 distances\n",
      "Working on county  40 distances\n",
      "Working on county  60 distances\n",
      "Working on county  80 distances\n",
      "Working on county  100 distances\n",
      "the max LAT-scaled distance between counties is 5.36822\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter user-picked max district diameter, or 0 to accept 5.36822  0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Working on county  0 neighbors\n",
      "Working on county  20 neighbors\n",
      "Working on county  40 neighbors\n",
      "Working on county  60 neighbors\n",
      "Working on county  80 neighbors\n",
      "Working on county  100 neighbors\n",
      "I have also identified each county's neighbors.  Let's visualize the counties with two or fewer neighbors\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#For corners and outcroppings, we fuse county clusters\n",
    "collapsedCountyList = list()  #VA has independent cities that we will reassign to parent counties\n",
    "print(\"Now finalize the map topology before any squish operations.  Plot countyPop/aDP\")\n",
    "preSquishCountyGeom = [countyGeom[c] for c in range(nCounties)]\n",
    "maxD = 0.\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"Working on county \",c,\"distances\")\n",
    "    if c not in cutCountyList:\n",
    "        plotPoly(countyGeom[c],0.2)\n",
    "        plotCenter(r3(countyPop[c]/aDP), countyGeom[c], 7 )\n",
    "        for cc in range(c+1, nCounties):\n",
    "            dist = getLongDist(countyCP[c],countyCP[cc],xScale)\n",
    "            if dist > maxD and cc not in cutCountyList:\n",
    "                maxD = dist\n",
    "                #print(c,cc,maxD)\n",
    "print(\"the max LAT-scaled distance between counties is\",r5(maxD))\n",
    "plotPoly(MAP)\n",
    "plotPoly(MAP.centroid.buffer(0.5*maxD))\n",
    "plt.show()\n",
    "inputD = float( input(\"enter user-picked max district diameter, or 0 to accept \"+str(r5(maxD))+\" \") )\n",
    "if inputD > 0:\n",
    "    maxD = inputD\n",
    "neighborCountyList = [list() for c in range(nCounties)]\n",
    "for c in uncutCountyList:\n",
    "    if c%20 == 0:\n",
    "        print(\"Working on county \",c,\"neighbors\")\n",
    "    for cc in uncutCountyList:\n",
    "        if cc > c and cc not in cutCountyList:  \n",
    "            if countyGeom[c].intersects(countyGeom[cc]) :\n",
    "                neighborCountyList[c].append(cc)\n",
    "                neighborCountyList[cc].append(c)\n",
    "print(\"I have also identified each county's neighbors.  Let's visualize the counties with two or fewer neighbors\")\n",
    "hasFewNeighborCs, has1neighborCs = list(), list()\n",
    "plotPoly(MAP,0.15)\n",
    "for c in uncutCountyList:\n",
    "    if len(neighborCountyList[c]) == 2:\n",
    "        hasFewNeighborCs.append(c)\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c+0.2,countyGeom[c])\n",
    "        for cc in neighborCountyList[c] :\n",
    "            plotPoly(countyGeom[c],0.5)\n",
    "    if len(neighborCountyList[c]) < 2:\n",
    "        has1neighborCs.append(c)\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c+0.1,countyGeom[c])\n",
    "        for cc in neighborCountyList[c] :\n",
    "            plotPoly(countyGeom[c],0.2)\n",
    "plt.show()   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "398fbc6d-3b05-4c1f-87cb-72d11cdd98bc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f9b3df93-d821-44ca-b4f4-b65d13baaffb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "continuing from above, develop corner county blocks from each low-pop corner county until it hits 0.25 of 753676\n",
      "checking if county 48 with pop 714342.0 and 1 or 2 neighbors is less pop than 188419\n",
      "checking if county 1 with pop 5240.0 and 1 or 2 neighbors is less pop than 188419\n",
      "checking if county 42 with pop 22035.0 and 1 or 2 neighbors is less pop than 188419\n",
      "checking if county 66 with pop 34962.0 and 1 or 2 neighbors is less pop than 188419\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Below I plot these again by county no, with faded neighboring counties\n",
      "0   [1, 76, 90, 43, 38, 63, 99, 75, 34, 29]\n",
      "1   [42, 7, 88, 97, 36]\n",
      "2   [66, 78, 94, 72, 38, 90, 1, 76]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now finalize the corner lists.  Remember, our avgDistrictPop and normal pop threshold are 753676.941 188419\n",
      "You may suggest [ [1,76,63,90,43,75,34,29,82,99,38], [42,7,88], [33,0] ] \n",
      "let's decide whether to delete, accept, or modify list [1, 76, 90, 43, 38, 63, 99, 75, 34, 29] with pop 187639.0\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list) [1,76,63,90,43,75,34,29,82,99,38]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, I will replace [1, 76, 90, 43, 38, 63, 99, 75, 34, 29] with [1, 76, 63, 90, 43, 75, 34, 29, 82, 99, 38]\n",
      "let's decide whether to delete, accept, or modify list [42, 7, 88, 97, 36] with pop 187342.0\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list) [42,7,88]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, I will replace [42, 7, 88, 97, 36] with [42, 7, 88]\n",
      "let's decide whether to delete, accept, or modify list [66, 78, 94, 72, 38, 90, 1, 76] with pop 180482.0\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list) 0\n",
      "enter 1 if you want to manually add another corner-county cluster 1\n",
      "Type in a [county list], where the corner county is first in the list.  Or type 0 to stop [33,0]\n",
      "enter 1 if you want to manually add another corner-county cluster 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Our final pops and fused-county lists are...\n",
      "211407.0 [1, 76, 63, 90, 43, 75, 34, 29, 82, 99, 38]\n",
      "82367.0 [42, 7, 88]\n",
      "83357.0 [33, 0]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "aDP = float(statePop)/nDistricts\n",
    "maxCCBratio = 1./4.  #adjustable max fraction of district pop for corner county blocks.  Let's try 3/16\n",
    "maxCCBpop = maxCCBratio * aDP\n",
    "print(\"continuing from above, develop corner county blocks from each low-pop corner county until it hits\",r3(maxCCBratio),\"of\",int(aDP) )\n",
    "CCBlist, CCBpop, passThruList = list(), list(), list()  #\"waiveThru\" counties get chance to join a cluster even if high pop\n",
    "nFuses = 0\n",
    "for c in set(has1neighborCs).difference(set(collapsedCountyList)):\n",
    "    print(\"checking if county\",c,\"with pop\",countyPop[c],\"and only 1 neighbor is less pop than\",int(maxCCBpop),\"vs districtPop\",int(aDP) )\n",
    "    if countyPop[c] > maxCCBpop:\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c,countyGeom[c])\n",
    "        nc = neighborCountyList[c][0]\n",
    "        plotPoly(countyGeom[nc],0.5)\n",
    "        plotPoly(MAP,0.2)\n",
    "        print(\"county\",c,\"has pop\",countyPop[c],\"and its only neighbor has pop\",countyPop[nc],\"vs districtPop\",aDP,\". Default = keep un-fused\")\n",
    "        print(\"enter 0 to keep\",c,\"as an unfused collection of units, 1 to fuse as one unit and stop, 2 to force-add at least the next closest county\")\n",
    "        fuseChoice = input(\"0, 1, or 2.  Any other input taken as a zero\")\n",
    "        if fuseChoice == 0:\n",
    "            keepUnfused = True\n",
    "            break\n",
    "        elif int(fuseChoice) == 1:\n",
    "            CCBlist.append([c])\n",
    "            CCBpop.append(countyPop[c])  \n",
    "            hasFewNeighborCs.append(c)  #this adds this [c] to the final list of fused units, but will fail to find more in below\n",
    "        elif int(fuseChoice) == 2:\n",
    "            CCBlist.append([c,nc ] )\n",
    "            CCBpop.append(countyPop[c] + countyPop[nc])\n",
    "            hasFewNeighborCs.append(c)\n",
    "            passThruList.append(c)   #pass on thru to the below 2neighbor logic even if too high-pop to qualify\n",
    "    else:\n",
    "        hasFewNeighborCs.append(c)  #normal case; we'll handle in next, more general, for loop            \n",
    "        \n",
    "for c in set(hasFewNeighborCs).difference(set(collapsedCountyList)):\n",
    "    print(\"checking if county\",c,\"with pop\",countyPop[c],\"and 1 or 2 neighbors is less pop than\",int(maxCCBpop) )\n",
    "    if countyPop[c] < maxCCBpop :\n",
    "        CCBlist.append([c])\n",
    "        CCBpop.append(countyPop[c])\n",
    "        CCBno = CCBlist.index([c])\n",
    "    if c in passThruList:\n",
    "        CCBno = CCBlist.index([c,neighborCountyList[c][0] ])\n",
    "    if countyPop[c] < maxCCBpop or c in passThruList:            \n",
    "        CCBstarter = c\n",
    "        canAdd = True\n",
    "        while canAdd:\n",
    "            nbrSet = set()\n",
    "            for cc in CCBlist[CCBno]:\n",
    "                nbrSet = ( nbrSet.union(set(neighborCountyList[cc])) ).difference(set(CCBlist[CCBno]))\n",
    "            nPop = [countyPop[cc] for cc in nbrSet]\n",
    "            nDist = [countyGeom[cc].centroid.distance(countyGeom[CCBstarter].centroid) for cc in nbrSet]\n",
    "            idx = np.argsort(nDist)\n",
    "            nbrList, newList = list(nbrSet), list()\n",
    "            for i in range(len(nDist)):  #add counties, closest to starter that will fit until over\n",
    "                cc = nbrList[idx[i]]\n",
    "                if CCBpop[CCBno] + countyPop[cc] < maxCCBpop:\n",
    "                    newList.append(cc)\n",
    "                    CCBlist[CCBno].append(cc)\n",
    "                    CCBpop[CCBno] += countyPop[cc]\n",
    "                    #print(\"adding county\",cc,\"with pop\",countyPop[cc],\"to list started by\",CCBstarter,\".Cluster pop now\",CCBpop[CCBno]  )\n",
    "            if newList == list():  #no eligible neighbor counties found; stop\n",
    "                canAdd = False\n",
    "                for cc in CCBlist[CCBno]:\n",
    "                    plotPoly(countyGeom[cc])\n",
    "                    plotCenter(CCBno,countyGeom[cc])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()\n",
    "                    \n",
    "print(\"Below I plot these again by county no, with faded neighboring counties\")\n",
    "plotPoly(MAP,0.15)\n",
    "for L in CCBlist:\n",
    "    print(CCBlist.index(L),\" \",L)\n",
    "    for c in L:\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c,countyGeom[c])\n",
    "        for cc in list(set(neighborCountyList[c]).difference(L) ):\n",
    "            plotPoly(countyGeom[cc],0.4)\n",
    "            plotCenter(cc,countyGeom[cc],8)\n",
    "plt.show()\n",
    "rejectList = list()\n",
    "print(\"Now finalize the corner lists.  Remember, our avgDistrictPop and normal pop threshold are\",r3(aDP), int(maxCCBpop))\n",
    "print(\"You may suggest [ [1,76,63,90,43,75,34,29,82,99,38], [42,7,88], [33,0] ] \")\n",
    "for i,L in enumerate(CCBlist):\n",
    "    if L[0] not in passThruList:  #if we forced the fused-counties list above, don't give option here to modify\n",
    "        print(\"let's decide whether to delete, accept, or modify list\",L,\"with pop\",CCBpop[i] )\n",
    "        isOK = input(\"enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list)\")\n",
    "        if not (isOK == 1 or isOK == str(1)) :\n",
    "            if isOK == 0 or isOK == str(0) :\n",
    "                rejectList.append(L)\n",
    "            else:\n",
    "                notGood = True\n",
    "                while notGood:       \n",
    "                    Lnew = ast.literal_eval(isOK)        \n",
    "                    if len(list(set(Lnew).difference(set([c for c in range(nCounties) ] )))) == 0:\n",
    "                        notGood = False\n",
    "                    else:\n",
    "                        print(\"Oops!  You didn't enter a valid list.  Try again as [\",L[0],\", n1, n2, ... ] where n1, n2 are county integers\")\n",
    "                        isOK = input(\"Try again here \")\n",
    "                print(\"OK, I will replace\",L,\"with\",Lnew)\n",
    "                CCBpop[i] = np.sum( [countyPop[c] for c in Lnew] )\n",
    "                CCBlist[i] = Lnew.copy()\n",
    "for L in rejectList:\n",
    "    del CCBpop[ CCBlist.index(L)]\n",
    "    del CCBlist[CCBlist.index(L)]\n",
    "stillAdding = True\n",
    "while stillAdding:\n",
    "    addMore = input(\"enter 1 if you want to manually add another corner-county cluster\")\n",
    "    if int(addMore) != 1:\n",
    "        stillAdding = False\n",
    "    else:\n",
    "        isOK = input(\"Type in a [county list], where the corner county is first in the list.  Or type 0 to stop\")\n",
    "        if isOK == 0 or isOK == str(0) :\n",
    "            print(\"OK, we'll stop adding corner clusters\")\n",
    "            stillAdding = False\n",
    "        else:\n",
    "            notGood = True\n",
    "            while notGood:       \n",
    "                Lnew = ast.literal_eval(isOK)        \n",
    "                if len(list(set(Lnew).difference(set([c for c in range(nCounties) ] )))) == 0:\n",
    "                    notGood = False\n",
    "                    for L in CCBlist:\n",
    "                        if set(L).intersection(set(Lnew)) != set(list()) :\n",
    "                            notGood = True\n",
    "                            print(\"OOPS! The following inputted counties are already in\",L,\":\",set(L).intersection(set(Lnew)) )\n",
    "                            isOK = input(\"Try again here \")\n",
    "                    if notGood == False:\n",
    "                        CCBlist.append(Lnew)\n",
    "                        CCBpop.append( np.sum( [countyPop[c] for c in Lnew] ) )\n",
    "                else:\n",
    "                    print(\"Oops!  You didn't enter a valid list.  Try again as [\",L[0],\", n1, n2, ... ] where n1, n2 are county integers\")\n",
    "                    isOK = input(\"Try again here \")\n",
    "print(\"Our final pops and fused-county lists are...\")\n",
    "allFusedCounties = list()\n",
    "CCBgeom = [dummyPoly for L in CCBlist ]\n",
    "CCBcp = list()\n",
    "for i, L in enumerate(CCBlist):\n",
    "    CCBcp.append( getHDcp([countyCP[c] for c in L], [countyPop[c] for c in L], [ j for j in range(len(L)) ] ) )\n",
    "    print(CCBpop[i],L)\n",
    "    pops, CPs = list(), list()\n",
    "    for c in L:\n",
    "        if c == L[0]:\n",
    "            CCBgeom[i] = countyGeom[c]\n",
    "        else:\n",
    "            CCBgeom[i] = CCBgeom[i].union(countyGeom[c])\n",
    "        allFusedCounties.append(c)\n",
    "        pops += countyPop[c]       #  IS THIS EVEN USED?\n",
    "        CPs.append(countyCP[c])   #  IS THIS EVEN USED?\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(i,countyGeom[c])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "206c9372-8ec8-4190-93ed-04df286466e0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now identify the border counties + border fused units, and interior small counties with pop < 15073\n",
      "We defined a total of 23 unit (but not corner-cluster) counties in the map\n",
      "excluding the cut-out districts and collapsed counties\n"
     ]
    }
   ],
   "source": [
    "maxWholeBorderCountyPop = 0.02 * aDP   #to encourage contiguity, border counties > 0.02 aDP will be forced whole\n",
    "maxInteriorBorderCountyPop = 0.02 * aDP\n",
    "print(\"now identify the border counties + border fused units, and interior small counties with pop <\", int(maxInteriorBorderCountyPop))\n",
    "unitCounties, borderCounties = list(), list()\n",
    "origMAP = MAP\n",
    "if MAP.geom_type == dummyPoly.geom_type:\n",
    "    MAPexterior = MAP.exterior\n",
    "else:\n",
    "    maxArea = 0\n",
    "    for geo in MAP.geoms:\n",
    "        if geo.area > maxArea:\n",
    "            MAPexterior = geo.exterior\n",
    "            maxArea = geo.area\n",
    "            MAP0 = geo\n",
    "    MAP = MAP0\n",
    "for c in set(uncutCountyList).difference(set(collapsedCountyList)):\n",
    "    if countyGeom[c].intersects(MAPexterior):\n",
    "        borderCounties.append(c)\n",
    "        if c not in allFusedCounties:\n",
    "            if countyPop[c] < maxWholeBorderCountyPop:\n",
    "                unitCounties.append(c)\n",
    "    else:\n",
    "        if countyPop[c] < maxInteriorBorderCountyPop and c not in allFusedCounties:\n",
    "            unitCounties.append(c)\n",
    "print(\"We defined a total of\",len(unitCounties),\"unit (but not corner-cluster) counties in the map\")\n",
    "print(\"excluding the cut-out districts and collapsed counties\")        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e0ff719c-59dc-4827-a522-11bd352f7524",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For this state, do we have a lot of populated fragmented VTDs?\n",
      "210 fragmented VTDs out of 10084\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FYI, here are the locations of fragmented VTDs with pop > 3000\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"For this state, do we have a lot of populated fragmented VTDs?\")\n",
    "nFragmentedVTDs,fragmentedVTDs = 0, list()\n",
    "for v in populatedTractList:\n",
    "    c = countyNo[v]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        if vtdGeom[v].geom_type != dummyPoly.geom_type :  #a multipoly vtd-based unit\n",
    "            nFragmentedVTDs +=1\n",
    "            fragmentedVTDs.append(v)\n",
    "print(len(fragmentedVTDs),\"fragmented VTDs out of\",nVTDs)\n",
    "fragPop = [tractPop[v] for v in fragmentedVTDs]\n",
    "plt.hist(fragPop)\n",
    "plt.show()\n",
    "print(\"FYI, here are the locations of fragmented VTDs with pop > 3000\")\n",
    "for v in fragmentedVTDs:\n",
    "    if tractPop[v] > 3000:\n",
    "        plotPoly(vtdGeom[v])\n",
    "plotPoly(MAP,0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "71d771f8-dbe2-48f9-a702-9f66a62d1174",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now writing the master list of units, which may be individual vtd's (+surrounds), whole counties, or corner county clusters\n",
      "I split up 210 fragmented VTDs. Now define unit neighbor lists and fuse geometries of surrounds.\n",
      "looking for surrounds, now working on vtd 0\n",
      "looking for surrounds, now working on vtd 500\n",
      "looking for surrounds, now working on vtd 1000\n",
      "looking for surrounds, now working on vtd 1500\n",
      "looking for surrounds, now working on vtd 2000\n",
      "looking for surrounds, now working on vtd 2500\n",
      "looking for surrounds, now working on vtd 3000\n",
      "looking for surrounds, now working on vtd 3500\n",
      "looking for surrounds, now working on vtd 4000\n",
      "looking for surrounds, now working on vtd 4500\n",
      "looking for surrounds, now working on vtd 5002\n",
      "looking for surrounds, now working on vtd 5502\n",
      "looking for surrounds, now working on vtd 6002\n",
      "looking for surrounds, now working on vtd 6502\n",
      "looking for surrounds, now working on vtd 7002\n",
      "looking for surrounds, now working on vtd 7502\n",
      "looking for surrounds, now working on vtd 8002\n",
      "looking for surrounds, now working on vtd 8502\n",
      "looking for surrounds, now working on vtd 9002\n",
      "looking for surrounds, now working on vtd 9502\n",
      "looking for surrounds, now working on vtd 10002\n",
      "special for IL , I believe that [10503, 10512] are surrounded by vtd (fragment) 10502 . Here, let me show you\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 to apply the surrounding operation 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "After surround checks, we appear to have 9678 building blocks defined. We captured 217 surrounded VTDs\n",
      "working on unit neighbor lists for county 0\n",
      "working on unit neighbor lists for county 20\n",
      "working on unit neighbor lists for county 40\n",
      "working on unit neighbor lists for county 60\n",
      "working on unit neighbor lists for county 80\n",
      "working on unit neighbor lists for county 100\n",
      "All done creating unit lists\n"
     ]
    }
   ],
   "source": [
    "#3/2/24 - split up all multipoly VTDs into fragments, divvy pop by area\n",
    "unitPop, unitCP, unitGeom, nbrUnitGeom, allUnits = list(), list(), list(), list(), list()\n",
    "vtdUnits, countyUnits, borderUnits = list(),list(),list()\n",
    "countyUnitList = [list() for c in range(nCounties) ]\n",
    "surroundedVTDs, surrounders = list(), list()  #vtds that are surrounded by another vtd - problem for later enclaves, xfer their pops to surrounders\n",
    "#These surrounded VTDs don't get transferred to the unit list\n",
    "print(\"Now writing the master list of units, which may be individual vtd's (+surrounds), whole counties, or corner county clusters\")\n",
    "for c in unitCounties:\n",
    "    unitCP.append(countyCP[c])\n",
    "    unitPop.append(countyPop[c])\n",
    "    unitGeom.append(   countyGeom[c] )\n",
    "    nbrUnitGeom.append(countyGeom[c] )\n",
    "    countyUnits.append(c)\n",
    "    allUnits.append(c+0.5)  #use non-integers to avoid vtd and county and cluster confusion\n",
    "\n",
    "nVTDneighbors = [0 for v in range(nVTDs)] #this loop -- just checking for surrounded VTDs\n",
    "lastVTDneighbor = [-999 for v in range(nVTDs)]\n",
    "\n",
    "nFragmentedVTDs,fragmentedVTDs, coastalFragmentedVTDs = 0, list(), list()  #a prev version treated coastal separately\n",
    "fragVTDgeom, parentVTDno, fragVTDpop = vtdGeom.to_list(), [v for v in range(nVTDs)], tractPop.to_list()  #these lists will expand to include vtd fragments \n",
    "origVTDgeom = vtdGeom.copy() #we create a parallel fragVTDgeom list which grabs the 1st fragment, then append fragments to the total list\n",
    "origVTDpop = tractPop.copy()\n",
    "VTDchildren = [[v] for v in range(nVTDs)]  #the list of all fragment numbers associated with the original VTD, including ones that get surrounded\n",
    "countyFragVTDset = [set(countyTractList[c]) for c in range(nCounties)]\n",
    "for v in populatedTractList:\n",
    "    c = countyNo[v]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        if vtdGeom[v].geom_type != dummyPoly.geom_type :  #a multipoly vtd-based unit\n",
    "            nFragmentedVTDs +=1\n",
    "            fragmentedVTDs.append(v)\n",
    "            geos, areas = [geo for geo in vtdGeom[v].geoms ], [geo.area for geo in vtdGeom[v].geoms]\n",
    "            for i, geo in enumerate(geos):\n",
    "                if i == 0:\n",
    "                    fragVTDgeom[v] = geo\n",
    "                    fragVTDpop[v] = tractPop[v] * areas[i] / np.sum(areas)  #overwrite, then distribute balance below\n",
    "                else:\n",
    "                    fNo = len(fragVTDgeom)\n",
    "                    fragVTDgeom.append(geo)\n",
    "                    fragVTDpop.append( tractPop[v] * areas[i] / np.sum(areas) )\n",
    "                    parentVTDno.append(v)\n",
    "                    countyFragVTDset[c].add(fNo )\n",
    "                    VTDchildren[v].append(fNo)\n",
    "                    nVTDneighbors.append(0)\n",
    "                    lastVTDneighbor.append(-999)\n",
    "                    \n",
    "print(\"I split up\",nFragmentedVTDs,\"fragmented VTDs. Now define unit neighbor lists and fuse geometries of surrounds.\")\n",
    "\n",
    "debugV = -7616\n",
    "for kk,V in enumerate(populatedTractList):\n",
    "    if kk%500 == 0:\n",
    "        print(\"looking for surrounds, now working on vtd\",V)\n",
    "    c = countyNo[V]\n",
    "    if c not in allFusedCounties and c not in unitCounties:\n",
    "        for v in VTDchildren[V]:\n",
    "            for vv in countyFragVTDset[c].difference({v}) :\n",
    "                if fragVTDgeom[vv].intersects(fragVTDgeom[v]):\n",
    "                    nVTDneighbors[v] +=1\n",
    "                    lastVTDneighbor[v] = vv\n",
    "                    if v == debugV:\n",
    "                        print(\"I just added neighbor\",vv,\"to magicV\",v)\n",
    "                #if nVTDneighbors[v] >= 4:  #Enough to have >=2 even after surrounds.  Will do full neighbor list later\n",
    "                #    break\n",
    "            #if STATE == \"TN\":  #Tennessee has a lot of discontiguous county fragments.  Force the nearest intracounty to be a neighbor\n",
    "            #    if nVTDneighbors[v] == 0:\n",
    "            #        listMinusSelf = list( countyFragVTDset[c].difference({v}) )\n",
    "            #        fragDist = [fragVTDgeom[vvv].distance(fragVTDgeom[v]) for vvv in listMinusSelf ]\n",
    "            #        minIndex = fragDist.index(np.min(fragDist))\n",
    "            #        vv = listMinusSelf[minIndex]\n",
    "            #        nVTDneighbors[v] +=1\n",
    "            #        lastVTDneighbor[v] = vv\n",
    "            #        print(\"I am forcing an intracounty neighbor for VTDfrag\",v,\"of vtd\",V,\"in county\",c,\"to be VTDfrag\",vv)\n",
    "            #        forcedPairList.append([v,vv])\n",
    "            if nVTDneighbors[v] < 4:  #OK if a vtd has only 1 intracounty neighbor IF it touches another county, it's not surrounded\n",
    "                for cc in neighborCountyList[c]:\n",
    "                    if fragVTDgeom[v].intersects(countyGeom[cc]):\n",
    "                        if cc not in unitCounties + allFusedCounties:\n",
    "                            for vv in countyFragVTDset[cc] :\n",
    "                                if fragVTDgeom[vv].intersects(fragVTDgeom[v]):\n",
    "                                    nVTDneighbors[v] +=1\n",
    "                                    lastVTDneighbor[v] = vv\n",
    "                            if nVTDneighbors[v] == 1:\n",
    "                                print(\"WARNING. vtd frag\",v,\"in county\",c,\"intersected county\",cc,\"but had no intracounty neighbors\")\n",
    "                                plotPoly(fragVTDgeom[v],2)\n",
    "                                plotCenter(\"iso\",fragVTDgeom[v])\n",
    "                                plotPoly(countyGeom[c])\n",
    "                                plotPoly(countyGeom[cc],0.2)\n",
    "                                plotCenter(cc, countyGeom[cc])\n",
    "                                plt.show()\n",
    "                        else:\n",
    "                            nVTDneighbors[v] +=1\n",
    "                            if nVTDneighbors[v] == 1:\n",
    "                                if STATE == \"TN\":  #for TN, we tolerate some discontiguous counties\n",
    "                                    print(\"vtd fragment\",v,\"with no neighbors in its county\",countyNo[parentVTDno[v]],\n",
    "                                          \"borders a unit or fused county\",cc)\n",
    "                                else:\n",
    "                                    raise Exception(\"ERROR! Neighborless vtd fragment\",v,\"neighbors a unit or fused county\",cc)                                \n",
    "            if v == debugV:\n",
    "                print(v,\"has\",nVTDneighbors[v],\"neighbors.  its last is\",lastVTDneighbor[v])\n",
    "                \n",
    "for loop in range(3): #to catch surrounds of surrounds\n",
    "    for V in populatedTractList:\n",
    "        c = countyNo[V]\n",
    "        if c not in allFusedCounties and c not in unitCounties: \n",
    "            for v in VTDchildren[V]:\n",
    "                if nVTDneighbors[v] == 1:\n",
    "                    vv = lastVTDneighbor[v]\n",
    "                    if v in surrounders:  #transferring surrounded of surrounds to master surrounder\n",
    "                        for sNo, s in enumerate(surroundedVTDs):\n",
    "                            if surrounders[sNo] == v:\n",
    "                                surrounders[sNo] = vv\n",
    "                    surroundedVTDs.append(v)\n",
    "                    surrounders.append(vv)\n",
    "                    nVTDneighbors[vv] -=1\n",
    "                    nVTDneighbors[v] -=1 #in case this surrounder becomes a later surroundee\n",
    "                    fragVTDpop[vv] += fragVTDpop[v]\n",
    "                    fragVTDpop[v] = 0\n",
    "                    if lastVTDneighbor[vv] == v:  #find another neighbor in case this surrounder is also a surroundee in loop 2\n",
    "                        for vvv in countyFragVTDset[c]:\n",
    "                            if vvv not in [v,vv]:\n",
    "                                if fragVTDgeom[vvv].intersects(fragVTDgeom[vv]):\n",
    "                                    lastVTDneighbor[vv] = vvv\n",
    "                    if lastVTDneighbor[vv] == v:\n",
    "                        print(\"WARNING.  We did not find another neighbor of surrounder\",vv,\"other than surroundee\",v)\n",
    "                    if loop > 0:\n",
    "                        print(\"On loop\",loop+1,\"for county\",c,\" we found that vtd frag\",v,\"now has only 1 neighbor\",vv)\n",
    "if STATE == \"IL\":  #state-specific manual surround enforcement\n",
    "    specialSurrounded = [10503, 10512]\n",
    "    specialSurrounder = 10502\n",
    "    print(\"special for\",STATE,\", I believe that\", specialSurrounded,\"are surrounded by vtd (fragment)\",specialSurrounder,\". Here, let me show you\")\n",
    "    c = countyNo[parentVTDno[specialSurrounder]]\n",
    "    plotPoly(countyGeom[c], 0.5)\n",
    "    for v in specialSurrounded:\n",
    "        plotPoly(fragVTDgeom[v])\n",
    "        plotCenter(v,fragVTDgeom[v])\n",
    "    plotPoly(fragVTDgeom[specialSurrounder],0.2)\n",
    "    plotCenter(specialSurrounder, fragVTDgeom[specialSurrounder], 8)\n",
    "    plt.show()\n",
    "    shouldIcombine = int(input(\"enter 1 to apply the surrounding operation\"))\n",
    "    if shouldIcombine == 1:\n",
    "        for v in specialSurrounded:\n",
    "            vv = specialSurrounder\n",
    "            if v in surrounders:  #transferring surrounded of surrounds to master surrounder\n",
    "                for sNo, s in enumerate(surroundedVTDs):\n",
    "                    if surrounders[sNo] == v:\n",
    "                        surrounders[sNo] = vv\n",
    "            surroundedVTDs.append(v)\n",
    "            surrounders.append(vv)\n",
    "            nVTDneighbors[vv] -=1\n",
    "            nVTDneighbors[v] = 0 #we are capturing all surroundees (some of whom may touch other surroundees)\n",
    "            fragVTDpop[vv] += fragVTDpop[v]\n",
    "            fragVTDpop[v] = 0\n",
    "\n",
    "\n",
    "for V in populatedTractList:\n",
    "    c = countyNo[V]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        for v in VTDchildren[V]:\n",
    "            if nVTDneighbors[v] >1:\n",
    "                unitCP.append(fragVTDgeom[v].centroid)\n",
    "                unitGeom.append(fragVTDgeom[v])\n",
    "                unitPop.append(fragVTDpop[v])   #for now, ratio pop by area, not block decomposition\n",
    "                vtdUnits.append(v)   #if a border unit, we'll catch in below big loop, after checking for surround\n",
    "                allUnits.append(v)\n",
    "#for V in populatedTractList:\n",
    "#    c = countyNo[V]\n",
    "#    if c not in allFusedCounties and c not in unitCounties:  \n",
    "#        for v in VTDchildren[V]: \n",
    "for V in populatedTractList:\n",
    "    c = countyNo[V]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        for v in VTDchildren[V]:\n",
    "            if nVTDneighbors[v] == 1:  #a surrounded VTD, transfer its pop to surrounder unit.  Don't bother with shifting centerpoints\n",
    "                print(\"somehow we missed 1-neighbor vtd frag\",v,\" with last vtd frag nbr\",lastVTDneighbor[v])\n",
    "            if nVTDneighbors[v] == 0 and v not in surroundedVTDs:\n",
    "                print(\"WARNING. unsurrounded vtd\",v,\"had no found neighbors\")\n",
    "\n",
    "for i, L in enumerate(CCBlist):\n",
    "    unitCP.append( CCBcp[i] )\n",
    "    unitPop.append(CCBpop[i])\n",
    "    unitGeom.append(   CCBgeom[i])\n",
    "    nbrUnitGeom.append(CCBgeom[i])\n",
    "    allUnits.append(i+0.25)  #use alt non-integers to avoid vtd and county and cluster confusion\n",
    "\n",
    "nUnits = len(allUnits)\n",
    "print(\"After surround checks, we appear to have\",nUnits,\"building blocks defined. We captured\",len(surroundedVTDs),\"surrounded VTDs\")\n",
    "\n",
    "unitNbrs = [list() for u in range(nUnits)]\n",
    "countyUnitList = [list() for c in range(nCounties)]\n",
    "for c in uncutCountyList:\n",
    "    for v in countyFragVTDset[c]:\n",
    "        if v in allUnits:\n",
    "            countyUnitList[c].append(allUnits.index(v))\n",
    "\n",
    "sketchyList = list()\n",
    "for c in uncutCountyList:\n",
    "    if c%20 == 0:\n",
    "        print(\"working on unit neighbor lists for county\",c)\n",
    "    if c not in allFusedCounties:  #see a separate loop below for cluster-cluster neighbors\n",
    "        if c in unitCounties:    \n",
    "            u = allUnits.index(c+0.5)\n",
    "            for cc in neighborCountyList[c]:\n",
    "                if cc not in allFusedCounties:\n",
    "                    if cc in unitCounties:\n",
    "                        unitNbrs[u].append(allUnits.index(cc+0.5))  #we'll catch the complement in the cc county's loop\n",
    "                    else:\n",
    "                        for uu in countyUnitList[cc] :\n",
    "                            if countyGeom[c].intersects(unitGeom[uu]):\n",
    "                                unitNbrs[u].append(uu)\n",
    "                                unitNbrs[uu].append(u)\n",
    "            for i,geo in enumerate(CCBgeom):\n",
    "                if geo.intersects(countyGeom[c]):\n",
    "                    unitNbrs[u].append(allUnits.index(i+0.25) )\n",
    "                    unitNbrs[allUnits.index(i+0.25) ].append(u)\n",
    "        else:  #non-unit county      \n",
    "            for u in countyUnitList[c] :\n",
    "                for uu in list( set(countyUnitList[c]).difference({u}) ) :\n",
    "                    if unitGeom[u].intersects(unitGeom[uu]):\n",
    "                        unitNbrs[u].append(uu )  #will catch complement later in this county's loop\n",
    "                for cc in neighborCountyList[c]:\n",
    "                    if cc not in allFusedCounties and cc not in unitCounties: #see an above block for handling unitCounties\n",
    "                        for uu in countyUnitList[cc]:\n",
    "                            if unitGeom[u].intersects(unitGeom[uu]):\n",
    "                                unitNbrs[u].append(uu )\n",
    "\n",
    "            for u in countyUnitList[c] :\n",
    "                for i,geo in enumerate(CCBgeom):\n",
    "                    if geo.intersects(unitGeom[u]):\n",
    "                        unitNbrs[u].append(allUnits.index(i+0.25) )\n",
    "                        unitNbrs[allUnits.index(i+0.25) ].append(u)\n",
    "                if len(unitNbrs[u]) == 0:\n",
    "                    print(\"ERROR - unit\",u,\" = vtd\",allUnits[u],\"in county\", c,\"has no neighbors\")\n",
    "                if len(unitNbrs[u]) == 1:  #after fragmentation, this unit appears surrounded.  Next block to confirm it has non-intracounty neighbors                       \n",
    "                    print(\"WARNING - unit\",u,\" = vtd\",allUnits[u],\"in county\", c,\"has only 1 neighbor=\",unitNbrs[u],\". Optional triage in next block\")\n",
    "                    sketchyList.append([u,unitNbrs[u][0] ] )\n",
    "\n",
    "CCBunits = CCBlist.copy()                        \n",
    "for i, geo in enumerate(CCBgeom):  #this loop: only cluster-cluster intersections.  Cluster-vtd and cluster-county neighbors already found above.\n",
    "    for ii in range(i+1,len(CCBgeom) ) :\n",
    "        if geo.intersects(CCBgeom[ii]):\n",
    "            if STATE != \"WA\" or i * ii != 3 :  #In WA, we don't allow ferry connection of Island to Clallam+Jefferson\n",
    "                unitNbrs[allUnits.index(i+0.25) ].append(allUnits.index(ii+0.25) ) #all CCB-county, CCB-vtd intersxns already covered\n",
    "                unitNbrs[allUnits.index(ii+0.25)].append(allUnits.index(i+0.25) )\n",
    "print(\"All done creating unit lists\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "94741893-6835-45ac-9793-64cbaf4823b2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Great! all units appear to have multiple neighbors; no checks needed.\n"
     ]
    }
   ],
   "source": [
    "if len(sketchyList) == 0:\n",
    "    print(\"Great! all units appear to have multiple neighbors; no checks needed.\")\n",
    "for L in sketchyList:  #hope that some of these flagged units picked up unit-county or CCB neighbors\n",
    "    print(\"sketchy unit\",L[0], \"has neighbor list\",unitNbrs[L[0]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "cb4277b4-d6ef-4c8c-aa23-6fde227379ff",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for u in range(nUnits):\n",
    "    if allUnits[u] - int(allUnits[u]) == 0.25:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "8378940d-4387-4188-8ae1-a62010500ecb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now build the border topology\n",
      "counties and clusters done, now working on (frag) vtd-based units\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Now build the border topology\")\n",
    "borderUnits, borderType = list(), list()\n",
    "for c in borderCounties:\n",
    "    if c in unitCounties:\n",
    "        borderUnits.append(allUnits.index(c+0.5))\n",
    "        borderType.append(\"county\")\n",
    "for i,L in enumerate(CCBlist):\n",
    "    if CCBgeom[i].intersects(MAPexterior):  #should usually be the case, but exception in VA\n",
    "        borderUnits.append(allUnits.index(i+0.25))\n",
    "        borderType.append(\"cluster\")\n",
    "print(\"counties and clusters done, now working on (frag) vtd-based units\")\n",
    "for c in borderCounties:\n",
    "    if c not in unitCounties + allFusedCounties:\n",
    "        for u in countyUnitList[c]:\n",
    "            if unitGeom[u].intersects(MAPexterior):\n",
    "                borderUnits.append(u)\n",
    "                borderType.append(\"vtd\")                \n",
    "if STATE == \"WA\":\n",
    "    print(\"adding a border unit between Island and Jefferson Counties, as these are only ferry-connected\")\n",
    "    borderUnits.append(2647)\n",
    "    borderType.append(\"vtd\")\n",
    "\n",
    "for i,b in enumerate(borderUnits):\n",
    "    plotPoly(unitGeom[b])\n",
    "    if borderType[i] == \"cluster\":\n",
    "        j = int(allUnits[b])\n",
    "        for c in CCBlist[j]:\n",
    "            plotPoly(countyGeom[c],0.2)\n",
    "            plotCenter(\"fused\",countyGeom[c], 6)\n",
    "for c in unitCounties:\n",
    "    plotPoly(countyGeom[c],0.4)\n",
    "    plotCenter(\"unit\",countyGeom[c],8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "937d923d-9e95-45e9-9aef-77cb4377781d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking that the list of borderUnits is contiguous all around\n",
      "number of border units = 271\n"
     ]
    }
   ],
   "source": [
    "print(\"checking that the list of borderUnits is contiguous all around\")\n",
    "print(\"number of border units =\",len(borderUnits))\n",
    "for u in borderUnits:\n",
    "    isUnbroken, smallPieceList = isContiguous(list(set(borderUnits).difference({u})),unitNbrs)\n",
    "    if not isUnbroken:\n",
    "        print(\"border is discontig if we skip\",u)\n",
    "        for uu in smallPieceList:\n",
    "            plotPoly(unitGeom[uu],0.5)\n",
    "            plotCenter(\"n\"+str(uu),unitGeom[uu])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "        plotPoly(unitGeom[u])\n",
    "        plt.show()\n",
    "        print(\"above is with unit numbers; below is VTDfrag nos\")\n",
    "        for uu in smallPieceList:\n",
    "            vv = allUnits[uu]\n",
    "            plotPoly(unitGeom[uu],0.5)\n",
    "            plotCenter(\"v\"+str(vv),unitGeom[uu],8)\n",
    "        v = allUnits[u]\n",
    "        plotCenter(v,unitGeom[u],8)\n",
    "        plotPoly(unitGeom[u])\n",
    "        plt.show()\n",
    "borderSet = set(borderUnits)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "359982d0-66ee-4ba1-8f0d-3c98356eab9c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4403, 4415, 4420]\n",
      "4403 4872\n",
      "4415 4878\n",
      "4420 4882\n"
     ]
    }
   ],
   "source": [
    "print(unitNbrs[4414])  #ignore this; was used to ID the IL surrounder + surroundees\n",
    "for u in unitNbrs[4414]:\n",
    "    print(u, allUnits[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "93603f77-77fa-4453-b54b-5ea07fcb6721",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here, we identify 'border' units that aren't needed to define the map border\n",
      "Bueno! no 'border units' that could be eliminated from the border set\n"
     ]
    }
   ],
   "source": [
    "print(\"here, we identify 'border' units that aren't needed to define the map border\")\n",
    "canBeRemoved, powerNeighbors = set(), set()\n",
    "for u in borderUnits:\n",
    "    uNeighbors = list(borderSet.intersection(set(unitNbrs[u])) )\n",
    "    if len(uNeighbors) < 2:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "        uu = uNeighbors[0]\n",
    "        otherBorderNeighbors = set(unitNbrs[uu]).intersection(borderSet).difference({u})\n",
    "        if len(otherBorderNeighbors) > 1:  #this neighbor of our 1-border-neighbor border unit makes a border chain without the problem border unit\n",
    "            canBeRemoved.add(u)\n",
    "            powerNeighbors.add(uu)\n",
    "        plotCenter(uu,unitGeom[uu],6)\n",
    "        plotPoly(unitGeom[uu],0.5)\n",
    "        for uuu in set(unitNbrs[uu]).intersection(borderSet).difference({u}):\n",
    "            plotPoly(unitGeom[uuu])\n",
    "            plotCenter(str(uuu)+\"=N of\"+str(uu),unitGeom[uuu])\n",
    "        for uuu in set(unitNbrs[u]).difference(borderSet):\n",
    "                plotCenter(uuu+0.1,unitGeom[uuu],6)\n",
    "                plotPoly(unitGeom[uuu],0.1)\n",
    "        c = countyNo[allUnits[u]]\n",
    "        #plotPoly(countyGeom[c] )\n",
    "        #plotCenter(c, countyGeom[c])\n",
    "        plt.show()\n",
    "if len(canBeRemoved) == 0:\n",
    "    print(\"Bueno! no 'border units' that could be eliminated from the border set\")\n",
    "else:\n",
    "    print(canBeRemoved,\"is the list of 1-neighbor 'border' units that can be eliminated from the border set\")\n",
    "    print(\"... as they are enveloped on the border; the enveloping border unit has two other map-border neighbors\")\n",
    "    yesRemove = input(\"enter 1 to remove these from the list of border units\")\n",
    "    if int(yesRemove) == 1:\n",
    "        canRemove = True\n",
    "        for uu in powerNeighbors:\n",
    "            testSet = (borderSet.difference(canBeRemoved)).difference({uu})\n",
    "            if not isContiguous(list(testSet),unitNbrs):\n",
    "                canRemove = False\n",
    "                print(\"We can't complete the border if unit\",uu,\"is not included in the ring\")\n",
    "        if canRemove:\n",
    "            borderSet = borderSet.difference(canBeRemoved)\n",
    "            borderList = list(borderSet)\n",
    "            borderUnits = list(borderSet)\n",
    "            print(\"Success! we removed\",canBeRemoved,\"from the list of borderUnits\")\n",
    "    else:\n",
    "        print(\"Fine, be that way.  Sheesh, I will keep them.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "b13c68e3-33ed-48b3-acca-78012ce0bf61",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here is the final border set\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for u in borderUnits:\n",
    "    plotPoly(unitGeom[u])\n",
    "print(\"here is the final border set\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "173bb175-312b-4d08-a5b5-80a1d5d70416",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n"
     ]
    }
   ],
   "source": [
    "print(isContiguous(borderUnits,unitNbrs)[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "fc1ae6e1-ef52-412b-a966-e9739071af8f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For safekeeping, write the unit topology to a file\n"
     ]
    }
   ],
   "source": [
    "date_ = \"26May24\"\n",
    "print(\"For safekeeping, write the unit topology to a file\")  \n",
    "unitParentVTDno = [-999 for u in range(nUnits)]\n",
    "for u in range(nUnits):    \n",
    "    if allUnits[u] %1 == 0:\n",
    "        v = allUnits[u]\n",
    "        unitParentVTDno[u] = parentVTDno[v]\n",
    "\n",
    "unitVTDlist = [list() for u in range(nUnits)]\n",
    "for u in range(nUnits):\n",
    "    if allUnits[u] % 1 == 0.5 :\n",
    "        c = int(allUnits[u])\n",
    "        unitVTDlist[u] = countyTractList[c].copy()\n",
    "    if allUnits[u] % 1 == 0.25 :\n",
    "        CCBnumber = int(allUnits[u])\n",
    "        for c in CCBlist[CCBnumber] :\n",
    "            unitVTDlist[u] += countyTractList[c]\n",
    "    if allUnits[u] % 1 == 0:\n",
    "        unitVTDlist[u] = [allUnits[u]]\n",
    "        #for i,uu in enumerate(surrounders):  #no longer tracked\n",
    "         #   if u == uu:\n",
    "         #       unitVTDlist[u].append(surroundedVTDs[i])\n",
    "                \n",
    "unitNo = [u for u in range(nUnits)]\n",
    "unitCPx, unitCPy = [unitCP[u].x for u in range(nUnits)], [unitCP[u].y for u in range(nUnits)]\n",
    "onBorder = [0 for u in range(nUnits)]\n",
    "for u in borderUnits:\n",
    "    onBorder[u] = 1\n",
    "nbrDF = pd.DataFrame( {\"unitNo\":unitNo,\"centroid x\":unitCPx,\"centroid y\":unitCPy,\"unitPop\":unitPop,\"onBorder\":onBorder,\n",
    "                       \"neighborList\":unitNbrs, \"unitVTDlist\":unitVTDlist, \"unitParentVTDno\": unitParentVTDno, \"allUnits\":allUnits} )\n",
    "outname = STATE+\"unitTopologies_\"+date_+\".csv\" \n",
    "outpath = \"state_map_files/\"+outname\n",
    "nbrDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "d4baaea4-7af4-4407-aeb3-f4291d335f89",
   "metadata": {},
   "outputs": [],
   "source": [
    "vtdGeom = tractGeom.copy()  #optional reset if we need to rerun the below clipPoly routine with alternate clipPolys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "abdd07e7-f9be-480a-9d3d-b3948eeaaa2e",
   "metadata": {},
   "outputs": [],
   "source": [
    "toSquishCountiesList = list()   #default; if we did not have any clipPoly's to move in\n",
    "nClips = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "4d5fdc3c-6126-4fa8-b484-1d0052c70aed",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "for many states we move in outcroppings via clipPoly's before running the wedgePoly solver\n",
      "adding code here to 'push in' state panhandles ...\n",
      "performing squish no 1 for state IL\n",
      "clipPoly 0 intersects [1, 34, 43, 63, 75, 76, 90] counties and a total of 69 units\n",
      "Here is the original cutLine and an alternate based on cut shapes\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "These are your orig (faint) and squished shapes for clip no 1 out of 2\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 when ready 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "performing squish no 2 for state IL\n",
      "clipPoly 1 intersects [7, 42] counties and a total of 27 units\n",
      "Here is the original cutLine and an alternate based on cut shapes\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "These are your orig (faint) and squished shapes for clip no 2 out of 2\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 when ready 1\n"
     ]
    }
   ],
   "source": [
    "#starting with MN, we moved the \"option2\" block earlier in the notebook, as we run it before running option 1 (as in other states)\n",
    "print(\"for many states we move in outcroppings via clipPoly's before running the wedgePoly solver\")\n",
    "vtdCP = tractCP.copy()\n",
    "#CODE TO SQUISH GEOMETRIES FROM CLIP LINES INTO THE MAP\n",
    "print(\"adding code here to 'push in' state panhandles ...\")\n",
    "trimDF = pd.read_csv(\"state_map_files/cutNclipPolyLists.csv\")\n",
    "stateRows = trimDF[\"state\"].to_list()\n",
    "DFrow = stateRows.index(STATE)\n",
    "nClips = trimDF[\"nClipPoly\"][DFrow]\n",
    "nCuts  = trimDF[\"nCutPoly\"][DFrow]\n",
    "#Adding in here trimming ops\n",
    "toSquishUnitsList = list()\n",
    "toSquishGeomsList = list()  #combined list of geoms we will squish (over all squish operations)\n",
    "toSquishCountiesList = list()\n",
    "squishedShapesList = list()   #unit shapes after squishing, list over all squish operations\n",
    "if nClips > 0:\n",
    "    clipPoints = ast.literal_eval(trimDF[\"clipPoints\"][DFrow])   #sets of four points\n",
    "    farPoints  = ast.literal_eval(trimDF[\"farPoints\"][DFrow])    #pairs of points\n",
    "    newFarPoints  = ast.literal_eval(trimDF[\"newFarPoints\"][DFrow])   #pairs\n",
    "    cPts = [Point(clipPoints[i][0],clipPoints[i][1]) for i in range(len(clipPoints)) ]\n",
    "    fPts = [Point(farPoints[i][0],farPoints[i][1]) for i in range(len(farPoints)) ]\n",
    "    nfPts = [Point(newFarPoints[i][0],newFarPoints[i][1]) for i in range(len(newFarPoints)) ]\n",
    "    \n",
    "    for clipNo in range(nClips):\n",
    "        print(\"performing squish no\",clipNo+1,\"for state\",STATE)\n",
    "        n0,n1,n2,n3 = int(4*clipNo), int(4*clipNo+1), int(4*clipNo+2), int(4*clipNo+3)\n",
    "        clipPoly = Polygon([cPts[n0],cPts[n1],cPts[n2],cPts[n3] ] )\n",
    "        cutLine = LineString([cPts[n0],cPts[n1]] )\n",
    "        farLine = LineString([fPts[int(2*clipNo)],fPts[int(2*clipNo+1)] ] )\n",
    "        newFarLine = LineString([nfPts[int(2*clipNo)],nfPts[int(2*clipNo+1)] ])\n",
    "        \n",
    "        toSquishCounties = list()\n",
    "        toSquishUnits = list()\n",
    "        for c in range(nCounties):\n",
    "            if clipPoly.intersects(countyGeom[c]):\n",
    "                toSquishCounties.append(c)\n",
    "                if clipPoly.contains(countyGeom[c]):\n",
    "                    toSquishUnits = toSquishUnits + countyTractList[c]\n",
    "                else:\n",
    "                    for t in countyTractList[c]:\n",
    "                        if clipPoly.contains(vtdCP[t]):\n",
    "                            toSquishUnits.append(t)\n",
    "        print(\"clipPoly\",clipNo,\"intersects\",toSquishCounties,\"counties and a total of\",len(toSquishUnits),\"units\")\n",
    "        toSquishGeomUnion = vtdGeom[toSquishUnits[0]]\n",
    "        toSquishGeoms = list()\n",
    "        for t in toSquishUnits:\n",
    "            toSquishGeomUnion = toSquishGeomUnion.union(vtdGeom[t])\n",
    "            toSquishGeoms.append(vtdGeom[t])\n",
    "        unclippedGeom = MAP.difference(toSquishGeomUnion)\n",
    "        altCutLine = toSquishGeomUnion.buffer(0.001).intersection(unclippedGeom)\n",
    "        print(\"Here is the original cutLine and an alternate based on cut shapes\")\n",
    "        #plotPoly(MAP,0.1)\n",
    "        plotPoly(cutLine.buffer(0.02))\n",
    "        plotPoly(altCutLine,0.1)\n",
    "        plt.show()\n",
    "        # could use altCutLine for a more accurate squish at the squish-no_squish boundary ...\n",
    "        #newShapes = squish(clippedGeomList, altCutLine, farLine, newFarLine)\n",
    "        squishedShapes = squish(toSquishGeoms, cutLine, farLine, newFarLine) #..but may distort results\n",
    "        toSquishUnitsList.append(toSquishUnits)\n",
    "        toSquishGeomsList.append(toSquishGeoms)\n",
    "        toSquishCountiesList.append(toSquishCounties)\n",
    "        squishedShapesList.append(squishedShapes)\n",
    "        for geo in toSquishGeoms:\n",
    "            plotPoly(geo,0.1)\n",
    "            plotPoly(geo.centroid.buffer(0.004),0.1)\n",
    "        for geo in squishedShapes:\n",
    "            plotPoly(geo)\n",
    "            plotPoly(geo.centroid.buffer(0.002),0.4)\n",
    "        print(\"These are your orig (faint) and squished shapes for clip no\",clipNo+1,\"out of\",nClips)\n",
    "        plt.show()\n",
    "        pause = input(\"enter 1 when ready\")    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "62667c48-6c66-4381-b01d-518af61651bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "#now apply the squish to all impacted vtds.  \"tractGeom\" will retain original vtd shapes, so we can reset if needed\n",
    "for i, vList in enumerate(toSquishUnitsList):\n",
    "    squishedShapes = squishedShapesList[i]\n",
    "    for j, v in enumerate(vList):\n",
    "        vtdGeom[v] = squishedShapes[j]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "7b967d22-41fb-454f-ae47-d72d712daa4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for t in range(nTracts):  #optional full state visualization after squish\n",
    "    if t not in allCutVTDs and t not in skipList:\n",
    "        plotPoly(vtdGeom[t])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9715564f-3b60-43e5-9f1f-02f3dcee3933",
   "metadata": {},
   "outputs": [],
   "source": [
    "c = 22  #pick a county for visualization if desired\n",
    "print(\"here are the faint(original) and squished shapes for county\",c)\n",
    "for t in countyTractList[c]:\n",
    "    plotPoly(vtdGeom[t])\n",
    "    plotPoly(tractGeom[t],0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "760bc48e-0236-4ad7-b3b8-d74795009f53",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"alternate simple approach for Florida Keys - translate all toward county CP\")\n",
    "c = 43\n",
    "vtdGeom = tractGeom.copy()  #a reset\n",
    "nTranslated = 0\n",
    "newCP = Point(-81, 25.1)\n",
    "for v in countyTractList[c]:\n",
    "    if clipPoly.contains(tractCP[v]):\n",
    "        xDelta, yDelta = newCP.x - tractCP[v].x, newCP.y - tractCP[v].y\n",
    "        xOFF, yOFF = 0.95 * xDelta, 0.95 * yDelta\n",
    "        vtdGeom[v] = translate(vtdGeom[v],xoff= xOFF, yoff=yOFF)\n",
    "        nTranslated +=1\n",
    "print(\"I translated\",nTranslated,\"vtds toward the center of county\",c)\n",
    "hdCP = [vtdGeom[v].centroid for v in range(nTracts)]\n",
    "countyGeom[c] = vtdGeom[countyTractList[c][0]]\n",
    "for v in countyTractList[c]:\n",
    "    countyGeom[c] = countyGeom[c].union(vtdGeom[v])\n",
    "    plotPoly(hdCP[v].buffer(0.03))\n",
    "plotPoly(countyGeom[c])\n",
    "unsquishedMAP = MAP\n",
    "MAP = countyGeom[uncutCountyList[0]]\n",
    "for c in uncutCountyList:\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "#plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "4ef91f8f-dabb-4c58-a8a4-bba8e725e586",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here we compute the map's convex hull. We can build out of whole counties or after squish operations.\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 to use squished shapes (e.g. for MD, MN), enter 0 for unclipped states 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on confirming HD center 0 is inside the map's convex hull\n",
      "working on confirming HD center 500 is inside the map's convex hull\n",
      "working on confirming HD center 1000 is inside the map's convex hull\n",
      "working on confirming HD center 1500 is inside the map's convex hull\n",
      "working on confirming HD center 2000 is inside the map's convex hull\n",
      "working on confirming HD center 2500 is inside the map's convex hull\n",
      "working on confirming HD center 3000 is inside the map's convex hull\n",
      "working on confirming HD center 3500 is inside the map's convex hull\n",
      "working on confirming HD center 4000 is inside the map's convex hull\n",
      "working on confirming HD center 4500 is inside the map's convex hull\n",
      "working on confirming HD center 5002 is inside the map's convex hull\n",
      "working on confirming HD center 5502 is inside the map's convex hull\n",
      "working on confirming HD center 6002 is inside the map's convex hull\n",
      "working on confirming HD center 6502 is inside the map's convex hull\n",
      "working on confirming HD center 7002 is inside the map's convex hull\n",
      "working on confirming HD center 7502 is inside the map's convex hull\n",
      "working on confirming HD center 8002 is inside the map's convex hull\n",
      "working on confirming HD center 8502 is inside the map's convex hull\n",
      "working on confirming HD center 9002 is inside the map's convex hull\n",
      "working on confirming HD center 9502 is inside the map's convex hull\n",
      "working on confirming HD center 10002 is inside the map's convex hull\n",
      "Here is the convex hull and shape and a dot map of the (shifted) unit centerpoints\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Note the MAP convex hull.  Overwrite with your own polygon if desired.\n"
     ]
    }
   ],
   "source": [
    "#OPTION 2 - draw polygonal HDs.  #REQUIRES CONSISTENT TREATMENT OF CCB'S \n",
    "#For GA, MA, MD, MN, NC we draw HDs for ALL vtds, even if they are in a CCB.  We use the clipPoly's to squish in the corners for these HD shapes\n",
    "#Not sure if below would work if we have cut districts AND squished-in corners\n",
    "#We normally draw for each (squished or orig) vtd.  Or, read in tract or blockgroup geometries, use those pops and unit centerpoints\n",
    "\n",
    "hdCP = [vtdGeom[v].centroid for v in range(nTracts)]  #remember, this is after any squish operation\n",
    "print(\"Here we compute the map's convex hull. We can build out of whole counties or after squish operations.\")\n",
    "useSquish = int(input(\"enter 1 to use squished shapes (e.g. for MD, MN), enter 0 for unclipped states\"))\n",
    "if useSquish == 1:\n",
    "    convexMAP = hdCP[countyTractList[uncutCountyList[0]][0]].buffer(0.1) \n",
    "    for v in range(nTracts):\n",
    "        if v not in skipList and v not in allCutVTDs:\n",
    "            convexMAP = convexMAP.union(hdCP[v].buffer(0.1))\n",
    "else:  #build the map via simple union of counties not wholly in fully cut-out districts\n",
    "    convexMAP = countyGeom[uncutCountyList[0]]\n",
    "    for c in uncutCountyList:\n",
    "        convexMAP = convexMAP.union(countyGeom[c])\n",
    "    #convexMAP = MAP.centroid\n",
    "    #for c in range(nCounties):\n",
    "    #    if c not in allFusedCounties:\n",
    "    #        convexMAP = convexMAP.union(countyGeom[c])\n",
    "MAPhull = convexMAP.convex_hull.buffer(0.01*convexMAP.area**0.5)\n",
    "plotPoly(MAPhull)\n",
    "popHDlist = list()\n",
    "for t in range(nTracts):\n",
    "    if t not in allCutVTDs and t not in skipList:  #keep low-pop tracts as VEST may have assigned voters to them\n",
    "        popHDlist.append(t)\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%500 == 0:\n",
    "        print(\"working on confirming HD center\",t,\"is inside the map's convex hull\")\n",
    "    if hdCP[t].disjoint(convexMAP.convex_hull):\n",
    "        plotPoly(hdCP[t].buffer(0.03))\n",
    "        hdCP[t] = nearest_points(convexMAP.convex_hull,hdCP[t])[0]\n",
    "        plotCenter(\"m\",hdCP[t])\n",
    "    else:\n",
    "        plotPoly(hdCP[t].buffer(0.01))\n",
    "plotPoly(convexMAP)\n",
    "plotPoly(convexMAP.convex_hull)\n",
    "plotPoly(MAPhull)\n",
    "for c in allFusedCounties:\n",
    "    plotPoly(countyGeom[c],0.2)\n",
    "print(\"Here is the convex hull and shape and a dot map of the (shifted) unit centerpoints\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Note the MAP convex hull.  Overwrite with your own polygon if desired.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "8393e96a-75c6-48ec-94e8-1f6fe58d31df",
   "metadata": {},
   "outputs": [],
   "source": [
    "nHDs = nTracts  #need to run this if we start option 2 from a vest list, not a previously run HD poly list\n",
    "HDcountyNo = countyNo.copy()\n",
    "populatedTractList = popHDlist.copy()  #nomenclature equivalency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "5ae791cd-d399-456f-a0cf-d3f215589177",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "special for IL.  To save time, narrow the list of close counties far from and near Chicago\n"
     ]
    }
   ],
   "source": [
    "print(\"special for IL.  To save time, narrow the list of close counties far from and near Chicago\")\n",
    "NEcountyList = [ 15, 48, 21, ]\n",
    "midCountyList = [ 98, 55, 3, 100, 70, 51, 18, 49, 44, 46, 31, 45, 52, 26, 37, 9, 91]\n",
    "farCountyList = list( set([c for c in range(nCounties)]) .difference(set(NEcountyList).union(set(midCountyList)) ) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "bcaf6ea2-1c3b-48c1-9ad6-937d7b7e4385",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let us establish the (post-squish) point-point distances for all HD centers, about 8 min for 4000-unit state\n",
      "working on tract-tract distances for unit 0 out of 10084 . Time = 0\n",
      "working on tract-tract distances for unit 400 out of 10084 . Time = 100\n",
      "working on tract-tract distances for unit 800 out of 10084 . Time = 209\n",
      "working on tract-tract distances for unit 1200 out of 10084 . Time = 335\n",
      "working on tract-tract distances for unit 1600 out of 10084 . Time = 462\n",
      "working on tract-tract distances for unit 2000 out of 10084 . Time = 578\n",
      "working on tract-tract distances for unit 2400 out of 10084 . Time = 654\n",
      "working on tract-tract distances for unit 2800 out of 10084 . Time = 728\n",
      "working on tract-tract distances for unit 3200 out of 10084 . Time = 778\n",
      "working on tract-tract distances for unit 3600 out of 10084 . Time = 858\n",
      "working on tract-tract distances for unit 4000 out of 10084 . Time = 970\n",
      "working on tract-tract distances for unit 4400 out of 10084 . Time = 1070\n",
      "working on tract-tract distances for unit 4800 out of 10084 . Time = 1163\n",
      "working on tract-tract distances for unit 5202 out of 10084 . Time = 1243\n",
      "working on tract-tract distances for unit 5602 out of 10084 . Time = 1318\n",
      "working on tract-tract distances for unit 6002 out of 10084 . Time = 1385\n",
      "working on tract-tract distances for unit 6402 out of 10084 . Time = 1447\n",
      "working on tract-tract distances for unit 6802 out of 10084 . Time = 1500\n",
      "working on tract-tract distances for unit 7202 out of 10084 . Time = 1546\n",
      "working on tract-tract distances for unit 7602 out of 10084 . Time = 1583\n",
      "working on tract-tract distances for unit 8002 out of 10084 . Time = 1613\n",
      "working on tract-tract distances for unit 8402 out of 10084 . Time = 1636\n",
      "working on tract-tract distances for unit 8802 out of 10084 . Time = 1652\n",
      "working on tract-tract distances for unit 9202 out of 10084 . Time = 1674\n",
      "working on tract-tract distances for unit 9602 out of 10084 . Time = 1687\n",
      "working on tract-tract distances for unit 10002 out of 10084 . Time = 1693\n",
      "All done; total elapsed  1693 seconds for IL with 17 districts to map\n"
     ]
    },
    {
     "data": {
      "image/png": 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48OCAmgut49xtfFVpaani4uLsKTk5uYd7CwAAQlXQQ05HR4dGjx6tZ599VrfddptmzZqlmTNnasWKFcHeVLcVFxfL5/PZU2Njo9MtAQCAXhL0kJOYmKiRI0cGzEtLS9OhQ4ckSV6vV5LU3NwcUNPc3Gwv83q9amlpCVh+9uxZHT16NKDmQus4dxtf5XK55Ha7AyYAAGCmoIeccePGqaGhIWDeZ599ppSUFElSamqqvF6vKisr7eV+v181NTXKysqSJGVlZen48eOqra21a6qqqtTR0aHMzEy7ZseOHTpz5oxdU1FRoeHDhwfcyQUAAPqmoIecefPmadeuXXr22Wf1xRdfaM2aNVq5cqUKCgokSREREZo7d66eeeYZbdiwQfv27dPDDz+spKQkTZ48WdJfz/zcc889mjlzpnbv3q0PPvhAhYWFmjZtmpKSkiRJDz74oKKjo5Wfn6/6+nqtXbtWS5cuVVFRUbB3yXEHRqQ53QIAAGEnKtgrvP3227V+/XoVFxfrqaeeUmpqql544QXl5eXZNY8//rhaW1s1a9YsHT9+XOPHj9eWLVsUExNj17z++usqLCzUxIkT1a9fP02ZMkXLli2zl8fFxendd99VQUGBxowZo2uuuUYLFiwIeJYOAADouyIsy7KcbsIpfr9fcXFx8vl8IT0+58CINKX9/sDX1qWvTte+6fuuQEdhoiROKvE53UW3VVbdoIl3/8HpNgAgZHX1/ZvPrgoj183fpPLZVefNk/hQRwAAvoqQE4Yqq25Q+ur0iy7vDD4AAPRlhJxQxdN6AQDoEUKOYf40/z+cbgEAgJBAyAEAAEYi5AAAACMRcgAAgJEIOQAAwEiEnBDDRzgAABAchBwAAGAkQg4AADASIScElZSUON0CAABhj5BjgK9+nhUAACDkhDWebgwAwMURcgAAgJEIOSHOu63O0e3zieYAgHBFyAEAAEYi5AAAACMRcsIEg4wBAOgeQg4AADASISeEOD3IGAAAkxByAACAkQg5AADASIQcAABgJEIOAAAwEiEHAAAYiZADAACMRMgBAMAA183fpPLZVaqsukHpq9Pt+eWzqyRJ6avT7QfLHhiRppKSkqBuv3N9nT2EAkIOAAAwEiEHAAAYiZADAACMRMgBAABGIuQAAAAjEXIAAICRCDkAAMBIhBwAAGAkQg4AADASIQcAABiJkGOwUHmsNgAATiDkAAAAIxFyQtiSqfc53QIAAGGLkAMAAIxEyAEAAEYi5AAAACMRcgAAgJEIOQAAwEiEHAAAYCRCDozn3VbndAsAAAcQcgAAgJEIOQAAwEiEHAAAYCRCDgAAMBIhBwAAGImQAwAAjETIMVz66nSnWwAAwBGEHAAAYCRCDgAAMBIhBwAAGKnXQ86iRYsUERGhuXPn2vNOnTqlgoICDRkyRAMGDNCUKVPU3Nwc8LpDhw4pNzdXV199tRISEvTYY4/p7NmzATXvvfeeRo8eLZfLpRtvvFGrVq3q7d0BAABholdDzp49e/SrX/1Kt9xyS8D8efPm6e2339abb76p7du368iRI/rud79rL29vb1dubq5Onz6tnTt3avXq1Vq1apUWLFhg1xw8eFC5ubn6zne+o7q6Os2dO1c//OEPtXXr1t7cJQAAECZ6LeScPHlSeXl5evnllzVo0CB7vs/n06uvvqrnnntOd999t8aMGaPXXntNO3fu1K5duyRJ7777rvbv369f//rXuvXWW3Xvvffq6aefVnl5uU6fPi1JWrFihVJTU7VkyRKlpaWpsLBQ//AP/6Dnn3++t3YJAACEkV4LOQUFBcrNzVV2dnbA/NraWp05cyZg/ogRIzRs2DBVV1dLkqqrq5Weni6Px2PX5OTkyO/3q76+3q756rpzcnLsdQBOKp9d5XQLANDnRfXGSt944w3t3btXe/bsOW9ZU1OToqOjFR8fHzDf4/GoqanJrjk34HQu71x2qRq/368vv/xSsbGx5227ra1NbW1t9td+v7/7OwcAAMJC0M/kNDY2as6cOXr99dcVExMT7NX3SGlpqeLi4uwpOTnZ6ZYAAEAvCXrIqa2tVUtLi0aPHq2oqChFRUVp+/btWrZsmaKiouTxeHT69GkdP3484HXNzc3yer2SJK/Xe97dVp1ff12N2+2+4FkcSSouLpbP57OnxsbGYOwyAAAIQUEPORMnTtS+fftUV1dnTxkZGcrLy7P/fdVVV6mystJ+TUNDgw4dOqSsrCxJUlZWlvbt26eWlha7pqKiQm63WyNHjrRrzl1HZ03nOi7E5XLJ7XYHTAAAwExBH5MzcOBA3XzzzQHz+vfvryFDhtjz8/PzVVRUpMGDB8vtdutHP/qRsrKydMcdd0iSJk2apJEjR+oHP/iBysrK1NTUpJ/97GcqKCiQy+WSJM2ePVsvvviiHn/8cT3yyCOqqqrSunXrtGnTpmDvEgAACEO9MvD46zz//PPq16+fpkyZora2NuXk5Oill16yl0dGRmrjxo169NFHlZWVpf79+2v69Ol66qmn7JrU1FRt2rRJ8+bN09KlSzV06FC98sorysnJcWKXAABAiLkiIee9994L+DomJkbl5eUqLy+/6GtSUlL0zjvvXHK9d911lz766KNgtAgAAAzDZ1cBAAAjEXIAAICRCDkAAMBIhBwAAGAkQg4AADASIQcAABiJkAMAAIxEyAEAAEYi5AAAACMRcgAAgJEIOQAAwEiEHAAAYCRCDgAAMBIhBwAAGImQAwAAjETIAQAARiLkAAAAIxFyAACAkQg5AADASIQcAABgJEIOAAB92JKp98m7rU4HRqSppKREKom7rHmhiJADAACMRMhBl6WvTne6BQAAuoyQAwAAjETIAQAARiLkAAAAIxFyAACAkQg5AADASIQcAABgJEIOAAAwEiEHAAAYiZADAACMRMgBAABGIuQAAAAjEXIAAICRCDkAAMBIhBwAAGAkQg4AADASIQcAABiJkAMAAIxEyAEAAEYi5AAAACMRcgAAgJEIOQAAwEiEHAAAYCRCDgAAMBIhBwAAGImQAwAAjETIwUX9af5/OLLdJVPvc2S7AACzEHIAAICRCDkAAMBIhBwAAGAkQg4AADASIQcAABiJkAMAAIxEyAEAAEYi5AAAACMRcgAAgJEIOQAAwEhBDzmlpaW6/fbbNXDgQCUkJGjy5MlqaGgIqDl16pQKCgo0ZMgQDRgwQFOmTFFzc3NAzaFDh5Sbm6urr75aCQkJeuyxx3T27NmAmvfee0+jR4+Wy+XSjTfeqFWrVgV7dwAAQJgKesjZvn27CgoKtGvXLlVUVOjMmTOaNGmSWltb7Zp58+bp7bff1ptvvqnt27fryJEj+u53v2svb29vV25urk6fPq2dO3dq9erVWrVqlRYsWGDXHDx4ULm5ufrOd76juro6zZ07Vz/84Q+1devWYO8SAAAIQ1HBXuGWLVsCvl61apUSEhJUW1urCRMmyOfz6dVXX9WaNWt09913S5Jee+01paWladeuXbrjjjv07rvvav/+/frd734nj8ejW2+9VU8//bSeeOIJlZSUKDo6WitWrFBqaqqWLFkiSUpLS9P777+v559/Xjk5OcHeLQAAEGZ6fUyOz+eTJA0ePFiSVFtbqzNnzig7O9uuGTFihIYNG6bq6mpJUnV1tdLT0+XxeOyanJwc+f1+1dfX2zXnrqOzpnMdF9LW1ia/3x8wAQAAM/VqyOno6NDcuXM1btw43XzzzZKkpqYmRUdHKz4+PqDW4/GoqanJrjk34HQu71x2qRq/368vv/zygv2UlpYqLi7OnpKTk3u8jwAAIDT1asgpKCjQp59+qjfeeKM3N9NlxcXF8vl89tTY2Oh0SwAAoJf0WsgpLCzUxo0btW3bNg0dOtSe7/V6dfr0aR0/fjygvrm5WV6v16756t1WnV9/XY3b7VZsbOwFe3K5XHK73QET+p4lU+9zugUAwBUQ9JBjWZYKCwu1fv16VVVVKTU1NWD5mDFjdNVVV6mystKe19DQoEOHDikrK0uSlJWVpX379qmlpcWuqaiokNvt1siRI+2ac9fRWdO5DgAA0LcF/e6qgoICrVmzRr/97W81cOBAewxNXFycYmNjFRcXp/z8fBUVFWnw4MFyu9360Y9+pKysLN1xxx2SpEmTJmnkyJH6wQ9+oLKyMjU1NelnP/uZCgoK5HK5JEmzZ8/Wiy++qMcff1yPPPKIqqqqtG7dOm3atCnYuwQAAMJQ0M/kLF++XD6fT3fddZcSExPtae3atXbN888/r/vuu09TpkzRhAkT5PV69e///u/28sjISG3cuFGRkZHKysrSQw89pIcfflhPPfWUXZOamqpNmzapoqJCo0aN0pIlS/TKK69w+zgAAJDUC2dyLMv62pqYmBiVl5ervLz8ojUpKSl65513Lrmeu+66Sx999FG3ewQAAObjs6sAAICRCDkAAMBIhBwEXfrqdKdbAACAkAMAAMxEyAEAAEYi5AAAACMRcmAU77a6iy4rKSm5Yn0AAJxHyMF5KqtucLoFAAB6jJADhIA/zf8Pp1sAAOMQcgAAgJEIOUAI4llDANBzhBwYbcnU+5xuAQDgEEIOEOLKZ1c53QIAhCVCDnqMQbMAgFBEyEFIutTzbgAA6ApCDgAAMBIhBwAAGImQA4QRxj8BQNcRctAjPM8FABCqCDkAAMBIhByYoSTO6Q4AACGGkIMuMe2TyYN9i7ppxydcXDd/k9MtAAhhhBx0y7kDX3ljBwCEMkIOAAAwEiEHAXr7c5J4knFoOjAizekWACDoCDnoNX0x0PAcG3QZg+WBXkfIwQXx/BsAQLgj5CBoevtSV3eUlJQ43UJYWDL1vh6vw6RjHUo/wwB6jpCDKyYYb6gAAHQVIQd9VrAH23KJDwjEGDU4jZCDbuMBbACAcEDIQUgzabxHWOjiHT9cegQQDgg5+Fo9HYwZUkGF23YvKqS+TwAQBIQcXBmEix5jzA8AdA8hB0HR03E6Jj1xlzFLABAaCDnoFZ13VVzJ8MI4EQDAuQg5gMO4DBXagv2AQJPOWgKhjpADhAgucwFAcBFyEFSVVTd0vfhCg5EZoGwz4UFqXEIE4CRCTh8RSmcJDoxIu+DtytzCfL4Lfd+C/b3stU+LD+HAGkr/HwD0HkJOHxDKZwSWTL2v995kz8E4iF72NYGG4w/ACYQchCzeGNGb+MRxwHyEHIdxiQbouW6NBUPPhfClSOBchBwH2Wcq+IWBMHXu2TYGGXff5R4zJ44145gQjgg5V8CVGHNypXGqH93VW2ct+VkEcDGEnCuE8SVXjonHOtwux1yJy7CXO6A+lAfiX4yJfygBVwIhxwGc1g9PnK4PdLE3XhNDJoDwRMgBHPTVMzRcermywu0MGYDuIeT0svPO2lxkkDFndwAACC5CzhXE7eLhg0tTl4exIwBCCSEHQJ/BJ74DfQshpzfx/Bsj8MbYM5zdOV84n9VlHBPCCSEHIIyGnd4OnqEYbLt91xo/1wAhxyn8dQsg2EL994rT4ZGzUH0PIaeXOH06mluRu+did7d1/lIMxwfIoXsYbA6Yh5CDPu2rYbQrf2ny1yAAhAdCDtAD183f5PhZM56xBFyc02fV4SxCDvB/OsczXOrSVGegcXpswVeDlXdbnQ6MSPvrL/RLDDgN9TEboYRLlED4I+QAfQyfLQWgrwj7kFNeXq7rrrtOMTExyszM1O7du51uCYb4ustQofCXflfOKHWerueylsGu0O3iTl+aBborrEPO2rVrVVRUpIULF2rv3r0aNWqUcnJy1NLS4nRrgKMINKGpL14u5K41OCmsQ85zzz2nmTNnasaMGRo5cqRWrFihq6++Wv/6r//qdGsAcEUwsNZ8/NFy+aKcbuBynT59WrW1tSouLrbn9evXT9nZ2aqurr7ga9ra2tTW1mZ/7fP5JEl+vz/o/bW1tckvS6fOnFFH60mdbG/v0Ty1tapDf9GXpzvU2tqh9i/bdaKb87qyn1+ebr3s9Z83rzWix/vd1tbWte9PW3COdVD2+//mdaXvnq6//cv2i+5P5/Y7j+G5dcXFxSouLr7ga9WFvnv1e9kFFzo+XVn3pV7X0fbXeRveTlX7l7E60dYqv9+vL0+3Bq3vS32fuvK6ztrzvr//933raD35/9fX1rXvZZd7bzvnmHVx3V/93dP+ZfvX7m9paWnA7/WeOvfnrqs/J191445P9MWEW4LWU3d1+eekLfD3RedrOn+GO3/+/X5/wP/JYL1Pda6v832kN95bO3Wu27KsSxdaYerw4cOWJGvnzp0B8x977DFr7NixF3zNwoULLUlMTExMTExMBkyNjY2XzApheybnchQXF6uoqMj+uqOjQ0ePHtWQIUMUERFxWev0+/1KTk5WY2Oj3G53sFo1Gses+zhm3ccx6x6OV/dxzLovWMfMsiydOHFCSUlJl6wL25BzzTXXKDIyUs3NzQHzm5ub5fV6L/gal8sll8sVMC8+Pj4o/bjdbn7Iu4lj1n0cs+7jmHUPx6v7OGbdF4xjFhcX97U1YTvwODo6WmPGjFFlZaU9r6OjQ5WVlcrKynKwMwAAEArC9kyOJBUVFWn69OnKyMjQ2LFj9cILL6i1tVUzZsxwujUAAOCwsA45U6dO1f/8z/9owYIFampq0q233qotW7bI4/FcsR5cLpcWLlx43mUwXBzHrPs4Zt3HMesejlf3ccy670ofswjL+rr7rwAAAMJP2I7JAQAAuBRCDgAAMBIhBwAAGImQAwAAjETI6aHy8nJdd911iomJUWZmpnbv3u10SyFrx44duv/++5WUlKSIiAi99dZbTrcU8kpLS3X77bdr4MCBSkhI0OTJk9XQ0OB0WyFr+fLluuWWW+wHjWVlZWnz5s1OtxVWFi1apIiICM2dO9fpVkJWSUmJIiIiAqYRI0Y43VZIO3z4sB566CENGTJEsbGxSk9P14cfftjr2yXk9MDatWtVVFSkhQsXau/evRo1apRycnLU0tLidGshqbW1VaNGjVJ5ebnTrYSN7du3q6CgQLt27VJFRYXOnDmjSZMmqbW11enWQtLQoUO1aNEi1dbW6sMPP9Tdd9+tv/u7v1N9fb3TrYWFPXv26Fe/+pVuucW5D6MMF9/85jf13//93/b0/vvvO91SyDp27JjGjRunq666Sps3b9b+/fu1ZMkSDRo0qPc3HpyPy+ybxo4daxUUFNhft7e3W0lJSVZpaamDXYUHSdb69eudbiPstLS0WJKs7du3O91K2Bg0aJD1yiuvON1GyDtx4oR10003WRUVFda3v/1ta86cOU63FLIWLlxojRo1yuk2wsYTTzxhjR8/3pFtcybnMp0+fVq1tbXKzs625/Xr10/Z2dmqrq52sDOYzOfzSZIGDx7scCehr729XW+88YZaW1v5qJcuKCgoUG5ubsDvNFzc559/rqSkJF1//fXKy8vToUOHnG4pZG3YsEEZGRn63ve+p4SEBN122216+eWXr8i2CTmX6X//93/V3t5+3tOVPR6PmpqaHOoKJuvo6NDcuXM1btw43XzzzU63E7L27dunAQMGyOVyafbs2Vq/fr1GjhzpdFsh7Y033tDevXtVWlrqdCthITMzU6tWrdKWLVu0fPlyHTx4UHfeeadOnDjhdGsh6Y9//KOWL1+um266SVu3btWjjz6qH//4x1q9enWvbzusP9YB6EsKCgr06aefcu3/awwfPlx1dXXy+Xz6t3/7N02fPl3bt28n6FxEY2Oj5syZo4qKCsXExDjdTli499577X/fcsstyszMVEpKitatW6f8/HwHOwtNHR0dysjI0LPPPitJuu222/Tpp59qxYoVmj59eq9umzM5l+maa65RZGSkmpubA+Y3NzfL6/U61BVMVVhYqI0bN2rbtm0aOnSo0+2EtOjoaN14440aM2aMSktLNWrUKC1dutTptkJWbW2tWlpaNHr0aEVFRSkqKkrbt2/XsmXLFBUVpfb2dqdbDHnx8fH6xje+oS+++MLpVkJSYmLieX9kpKWlXZFLfIScyxQdHa0xY8aosrLSntfR0aHKykqu/yNoLMtSYWGh1q9fr6qqKqWmpjrdUtjp6OhQW1ub022ErIkTJ2rfvn2qq6uzp4yMDOXl5amurk6RkZFOtxjyTp48qT/84Q9KTEx0upWQNG7cuPMeffHZZ58pJSWl17fN5aoeKCoq0vTp05WRkaGxY8fqhRdeUGtrq2bMmOF0ayHp5MmTAX/pHDx4UHV1dRo8eLCGDRvmYGehq6CgQGvWrNFvf/tbDRw40B7vFRcXp9jYWIe7Cz3FxcW69957NWzYMJ04cUJr1qzRe++9p61btzrdWsgaOHDgeWO8+vfvryFDhjD26yJ+8pOf6P7771dKSoqOHDmihQsXKjIyUg888IDTrYWkefPm6Vvf+paeffZZff/739fu3bu1cuVKrVy5svc37sg9XQb55S9/aQ0bNsyKjo62xo4da+3atcvplkLWtm3bLEnnTdOnT3e6tZB1oeMlyXrttdecbi0kPfLII1ZKSooVHR1t/c3f/I01ceJE691333W6rbDDLeSXNnXqVCsxMdGKjo62rr32Wmvq1KnWF1984XRbIe3tt9+2br75ZsvlclkjRoywVq5ceUW2G2FZltX7UQoAAODKYkwOAAAwEiEHAAAYiZADAACMRMgBAABGIuQAAAAjEXIAAICRCDkAAMBIhBwAAGAkQg4AADASIQcAABiJkAMAAIxEyAEAAEb6f3EBquVrh4zuAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "our maxD was 5.368215683577071\n"
     ]
    }
   ],
   "source": [
    "#continuing option 2 ....... ##########  THIS IS FOR TRACT - TRACT, despite the \"unit\" nomenclature\n",
    "print(\"Let us establish the (post-squish) point-point distances for all HD centers, about 8 min for 4000-unit state\")\n",
    "#NOTE: FOR LARGE STATES, RESTRICT THE SEARCH TO COUNTIES WITHIN A 3/SQRT(nDistrict) DIAMETER OF THE HOME UNIT\n",
    "uuDist = [[int(maxD+1) for t in range(nHDs)] for t in range(nHDs)] #default: too big to capture\n",
    "closeCountyList = [list() for c in range(nCounties)]\n",
    "closeCountyDist = maxD   #min(maxD,3./float(nDistricts)**0.5 * maxD )  #use above maxD for these counties as well\n",
    "xScaleSquared = xScale*xScale\n",
    "if STATE == \"IL\":\n",
    "    closeCountyList = [[i for i in range(nCounties)] for c in range(nCounties)]\n",
    "    for c in range(nCounties):\n",
    "        if c in NEcountyList:\n",
    "            closeCountyList[c] = NEcountyList + midCountyList\n",
    "        if c in farCountyList:\n",
    "            closeCountyList[c] = farCountyList + midCountyList\n",
    "elif nDistricts < 10: #closeCountyDist >= maxD:  #small state\n",
    "    closeCountyList = [[i for i in range(nCounties)] for c in range(nCounties)]  #all counties are close enough\n",
    "    \n",
    "else:\n",
    "    for c in uncutCountyList:\n",
    "        closeCountyList[c].append(c)\n",
    "        for cc in range(c+1,nCounties):\n",
    "            if cc in uncutCountyList:\n",
    "                if cc in neighborCountyList[c]:\n",
    "                    closeCountyList[c].append(cc)\n",
    "                    closeCountyList[cc].append(c)\n",
    "                else:    \n",
    "                    dist = getLongDist(countyCP[c], countyCP[cc],xScale)\n",
    "                    if dist < closeCountyDist:\n",
    "                        closeCountyList[c].append(cc)\n",
    "                        closeCountyList[cc].append(c)\n",
    "startTime = time.time()\n",
    "\n",
    "for i,t in enumerate(populatedTractList):\n",
    "    if i %400 == 0:\n",
    "        print(\"working on tract-tract distances for unit\",t,\"out of\",nHDs,\". Time =\",int(time.time() - startTime))\n",
    "    uuDist[t][t] == 0.\n",
    "    for tt in populatedTractList:\n",
    "        if tt > t and (HDcountyNo[tt] in closeCountyList[HDcountyNo[t]] or HDcountyNo[t] == HDcountyNo[tt]):  #time-saver; do the triangle matrix\n",
    "                dist = getLongDist(hdCP[t], hdCP[tt],xScale)\n",
    "                uuDist[t][tt], uuDist[tt][t] = dist, dist\n",
    "print(\"All done; total elapsed \",int(time.time()-startTime),\"seconds for\",STATE,\"with\",nDistricts,\"districts to map\" )\n",
    "plt.hist(uuDist)\n",
    "plt.show()\n",
    "print(\"our maxD was\",maxD)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "2f392acb-ba52-4343-80ae-a58ba0b57366",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "similar to above, but for angles\n",
      "working on unit-unit angles for unit 0 out of 10084 . Time = 0\n",
      "working on unit-unit angles for unit 400 out of 10084 . Time = 53\n",
      "working on unit-unit angles for unit 800 out of 10084 . Time = 109\n",
      "working on unit-unit angles for unit 1200 out of 10084 . Time = 172\n",
      "working on unit-unit angles for unit 1600 out of 10084 . Time = 241\n",
      "working on unit-unit angles for unit 2000 out of 10084 . Time = 300\n",
      "working on unit-unit angles for unit 2400 out of 10084 . Time = 340\n",
      "working on unit-unit angles for unit 2800 out of 10084 . Time = 378\n",
      "working on unit-unit angles for unit 3200 out of 10084 . Time = 404\n",
      "working on unit-unit angles for unit 3600 out of 10084 . Time = 445\n",
      "working on unit-unit angles for unit 4000 out of 10084 . Time = 501\n",
      "working on unit-unit angles for unit 4400 out of 10084 . Time = 554\n",
      "working on unit-unit angles for unit 4800 out of 10084 . Time = 601\n",
      "working on unit-unit angles for unit 5202 out of 10084 . Time = 642\n",
      "working on unit-unit angles for unit 5602 out of 10084 . Time = 681\n",
      "working on unit-unit angles for unit 6002 out of 10084 . Time = 716\n",
      "working on unit-unit angles for unit 6402 out of 10084 . Time = 748\n",
      "working on unit-unit angles for unit 6802 out of 10084 . Time = 775\n",
      "working on unit-unit angles for unit 7202 out of 10084 . Time = 799\n",
      "working on unit-unit angles for unit 7602 out of 10084 . Time = 818\n",
      "working on unit-unit angles for unit 8002 out of 10084 . Time = 834\n",
      "working on unit-unit angles for unit 8402 out of 10084 . Time = 848\n",
      "working on unit-unit angles for unit 8802 out of 10084 . Time = 856\n",
      "working on unit-unit angles for unit 9202 out of 10084 . Time = 867\n",
      "working on unit-unit angles for unit 9602 out of 10084 . Time = 874\n",
      "working on unit-unit angles for unit 10002 out of 10084 . Time = 877\n",
      "All done with angles; total elapsed seconds = 877\n"
     ]
    }
   ],
   "source": [
    "#continuing option 2 \n",
    "print(\"similar to above, but for angles\")  #convention is angle[a][b] is from a to b\n",
    "uuAngle = [[0. for t in range(nHDs)] for t in range(nHDs)]\n",
    "\n",
    "pi = 3.141592653\n",
    "twoPi = pi*2.\n",
    "startTime = time.time()\n",
    "for i, t in enumerate(populatedTractList):\n",
    "    if i %400 == 0:\n",
    "        print(\"working on unit-unit angles for unit\",t,\"out of\",nHDs,\". Time =\",int(time.time() - startTime)  )\n",
    "    for tt in populatedTractList:\n",
    "        if tt > t and (HDcountyNo[tt] in closeCountyList[HDcountyNo[t]] or HDcountyNo[t] == HDcountyNo[tt]):  #time-saver; do the triangle matrix\n",
    "            angLE = math.atan2(hdCP[tt].y - hdCP[t].y, xScale * (hdCP[tt].x - hdCP[t].x) )\n",
    "            uuAngle[t][tt], uuAngle[tt][t] = angLE % twoPi, (angLE + pi) % twoPi\n",
    "print(\"All done with angles; total elapsed seconds =\",int(time.time()-startTime) )\n",
    "#plt.hist(uuAngle)\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "4cc54eba-ca37-4680-9699-37332133afb8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "753676.941 17 12812508.0 17.0 12812508.0\n",
      "12812508.0 12812508 1.0\n"
     ]
    }
   ],
   "source": [
    "print(r3(aDP), nDistricts, statePop, statePop/aDP, trueStatePop)\n",
    "HDweight = [0 for t in range(nHDs)]\n",
    "for t in populatedTractList:\n",
    "    HDweight[t] = tractPop[t] / trueStatePop #skipping the cutList tracts\n",
    "print(statePop,np.sum([tractPop[t] for t in populatedTractList]), r5(np.sum(HDweight))) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "dac2348a-060a-40a9-beeb-02ff70ec1aa1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RUN FOR ALL STATES.for extended peninsulas, need to broaden the 'neighborCountyList' to include all co-squished counties' neighbors\n"
     ]
    }
   ],
   "source": [
    "print(\"RUN FOR ALL STATES.for extended peninsulas, need to broaden the 'neighborCountyList' to include all co-squished counties' neighbors\")\n",
    "opt2nbrCtyList = [neighborCountyList[c].copy() for c in range(nCounties)]\n",
    "for i in range(nClips):\n",
    "    cList = toSquishCountiesList[i]\n",
    "    for c in cList:\n",
    "        for cc in cList:\n",
    "            for ccc in neighborCountyList[cc]:\n",
    "                if ccc not in opt2nbrCtyList[c] and ccc != c:\n",
    "                    opt2nbrCtyList[c].append(ccc)\n",
    "#for c in range(nCounties):\n",
    "#    for cc in opt2nbrCtyList[c]:\n",
    "#        plotPoly(countyGeom[cc])\n",
    "#    plotCenter(c,countyGeom[c])\n",
    "#    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "3873aaa2-0c39-4ac0-99c3-92dd7c18c555",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here is the main code to draw 4-wedge Home Districts for each populated HD centerpoint\n",
      "For each Home District, we will consider a wedge as one-from-full when it is within 1016.664 of targetWedgePop\n",
      "I am working on HD number 0 of 10084 HDs.  Elapsed sec = 0\n",
      "I am working on HD number 400 of 10084 HDs.  Elapsed sec = 107\n",
      "I am working on HD number 800 of 10084 HDs.  Elapsed sec = 204\n",
      "I am working on HD number 1200 of 10084 HDs.  Elapsed sec = 308\n",
      "I am working on HD number 1600 of 10084 HDs.  Elapsed sec = 392\n",
      "I am working on HD number 2000 of 10084 HDs.  Elapsed sec = 483\n",
      "I am working on HD number 2400 of 10084 HDs.  Elapsed sec = 583\n",
      "I am working on HD number 2800 of 10084 HDs.  Elapsed sec = 675\n",
      "I am working on HD number 3200 of 10084 HDs.  Elapsed sec = 769\n",
      "I am working on HD number 3600 of 10084 HDs.  Elapsed sec = 848\n",
      "I am working on HD number 4000 of 10084 HDs.  Elapsed sec = 1028\n",
      "I am working on HD number 4400 of 10084 HDs.  Elapsed sec = 1228\n",
      "I am working on HD number 4800 of 10084 HDs.  Elapsed sec = 1365\n",
      "I am working on HD number 5202 of 10084 HDs.  Elapsed sec = 1541\n",
      "I am working on HD number 5602 of 10084 HDs.  Elapsed sec = 1750\n",
      "I am working on HD number 6002 of 10084 HDs.  Elapsed sec = 1961\n",
      "I am working on HD number 6402 of 10084 HDs.  Elapsed sec = 2170\n",
      "I am working on HD number 6802 of 10084 HDs.  Elapsed sec = 2371\n",
      "I am working on HD number 7202 of 10084 HDs.  Elapsed sec = 2562\n",
      "I am working on HD number 7602 of 10084 HDs.  Elapsed sec = 2751\n",
      "I am working on HD number 8002 of 10084 HDs.  Elapsed sec = 2896\n",
      "I am working on HD number 8402 of 10084 HDs.  Elapsed sec = 2983\n",
      "I am working on HD number 8802 of 10084 HDs.  Elapsed sec = 3077\n",
      "I am working on HD number 9202 of 10084 HDs.  Elapsed sec = 3158\n",
      "I am working on HD number 9602 of 10084 HDs.  Elapsed sec = 3259\n",
      "I am working on HD number 10002 of 10084 HDs.  Elapsed sec = 3370\n",
      "3395.758 seconds elapsed. All done computing HD shapes and tractlists.  Here is a histogram of vtd usage.\n",
      "vtd avg and sd usage are 0.99945 0.10917\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are your HD pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing option 2 .......\n",
    "# BELOW modified Dec23 to use inter-unit distances and angles, (counties still wedgeIntersxn) otherwise similar to HD2\n",
    "# --THIS ESSENTIALLY TAKES THE ORIGINAL TRACT-BASED HD centerpoints, and redraws HD2 districts after convexifying corners and convex_hull\n",
    "print(\"Here is the main code to draw 4-wedge Home Districts for each populated HD centerpoint\") \n",
    "#this is a hybrid of HD2 and the organic code, in that all wedge tracts must be in a chain of neighboring counties\n",
    "#General sequence: draw 4 equi-angle wedges with random starting orientation.  If not all can fill a quarter aDP ...\n",
    "# ... find the closest map boundary point to the tract center point in the shortest wedge.  Orient the 0th wedge to face this point\n",
    "# ... determine the \"maxWedgePop\" for this short wedge and the other three wedges extended past the boundary\n",
    "# ...  if this results in only one short wedge, or opposing short wedges, adjust wedge angles\n",
    "# Regardless of whether we re-oriented or adjusted angles, compute each wedgePop for infinite radius\n",
    "#   ... then adjust other targetWedgePops if some found to be short.\n",
    "#   ... for non-shorted wedges, use bisection method to adjust radius to meet targetWedgePop\n",
    "#   ... once total HDpop within tolerance, add/subtract a tract fraction to fulfill HDpop\n",
    "#  create a list of fully used tracts per HD, save the tract# of the split tract and its fractional use\n",
    "#  Compute tractUse across all HDs at the end from the tractUsageLists.  Defer patching and partisan calcs to another code\n",
    "\n",
    "pi=3.1415926536\n",
    "#MAPhull = MAP.convex_hull #used for exitAngle calc.  Defined in an above block to allow user modification\n",
    "nWedges = 4  #number of wedges per home district polygon  \n",
    "avgWedgeAngle = 2.*pi / nWedges\n",
    "angle, angle2, wedgePoly = [0.]*nWedges, [0.]*nWedges, [dummyPoly]*nWedges  #start and stop angle of each wedge\n",
    "pt1, pt2, pt3 = [Point(0,0)]*nWedges, [Point(0,0)]*nWedges, [Point(0,0)]*nWedges #these four define the polygon wedge for a growing home district\n",
    "tractUse = [0.] * nHDs  #this will store how much we use this tract in ALL HD's vs. expectation\n",
    "HDtractList = [list()]*nHDs\n",
    "splitTractNo = [-999]*nHDs  #the tract that is only partially used to finish each HD\n",
    "splitTractUse = [0.]*nHDs  #and this is what fraction of the split tract is included\n",
    "HDvPop = [0.]*nHDs\n",
    "#HDweight = [tractPop[t] / (statePop - excludedPop) for t in range(nTracts)]  #relative weight of each drawn HD\n",
    "HDPoly1 = [dummyPoly]*nHDs  #final 4-wedge shape, unionized from blockgroups / tracts\n",
    "HDarea = [0.]*nHDs  #geographical area of each home district (after boundary trim)\n",
    "HDradius = [[0.]*nWedges for t in range(nHDs)] #final wedge length for each Home District wedge\n",
    "HDangle = [[0.]*nWedges for t in range(nHDs)] #final starting angle for each HD wedge\n",
    "angle0 = [-999.] * nHDs  #orientation of 0th wedge.  Random except re-oriented if we are near-boundary\n",
    "avgTractPop = statePop/len(populatedTractList)\n",
    "tolerPops = [0.8 * avgTractPop, 0.5 * np.max(tractPop)]  #threshold gap before adding one more unit to a wedge \n",
    "tolerPop = tolerPops[0]\n",
    "print(\"For each Home District, we will consider a wedge as one-from-full when it is within\",r3(tolerPops[0]),\"of targetWedgePop\")\n",
    "tractPrintInterval = 400  #for tracking progress\n",
    "levelL = 0.36 #sqrt(pop) for angle=std  These two control distortion in wedge angles relative to wedgePop shortness\n",
    "maxAngleRatio = 1.9  #for tightening tract weighting near boundaries  #HD2\n",
    "maxAngle = 1.8*pi/2. # limit to avoid wedges too close to half a pie\n",
    "minAdjRatio = 0.5  #min ratio of pop of adjacent wedge (to min wedge) to targetWedgePop to not consider this a corner HD\n",
    "maxUncap = 0.5 #the max ratio of uncaptured pop in a maxWedge vs. target wedge pop that we will not stretch to include (7/23)\n",
    "oppWt = 0.0    #the fraction of gap between normal targetWedgePop and the minWedgePop that we allow the opposite wedge to add to tgtPop = minWedgePop\n",
    "maxWedgePop = [0.] * nWedges  #wedge pop if we explode wedge to maximum radius\n",
    "printDebug = \"no\"\n",
    "codeStartTime = time.time()\n",
    "hdCPpop = [HDweight[t] * statePop for t in range(nHDs)]\n",
    "countyHDlist = [list() for c in range(nCounties)]\n",
    "for t in populatedTractList:\n",
    "    countyHDlist[HDcountyNo[t]].append(t)\n",
    "\n",
    "for kkkj, t in enumerate(populatedTractList):  #range(nTracts) : #loop on each tract. \n",
    "    hC = HDcountyNo[t]     #this tract's home county\n",
    "    HDtractList[t] = [t] #seed the list of tracts in this HD\n",
    "    wedgeList = [list() for w in range(nWedges)]   #list of each wedge's tracts, excluding home tract\n",
    "    barredList = list()  #list of wedge numbers for which we are barred from altering their targetWedgePops\n",
    "    if (kkkj % tractPrintInterval) == 0 : \n",
    "        print(\"I am working on HD number {0} of {1} HDs.  Elapsed sec = {2}\".format(t,nHDs,int(time.time()-codeStartTime) ) )  \n",
    "    nActiveWedges = nWedges #active wedges have not run over boundary\n",
    "    wedgePop = [0.]*nWedges\n",
    "    targetWedgePop = [aDP / nWedges]*nWedges  #at beginning, split districtPop equally among wedges\n",
    "    \n",
    "    angle0[t] = random.uniform(0,2.*pi)  #imparts random orientation to the midangle of our starting wedge\n",
    "    wedgeAngle = [avgWedgeAngle for w in range(nWedges) ] #reset to equi-angle when starting each tract\n",
    "    for nW in range(nWedges-1):\n",
    "        wedgeAngle[nW] += random.uniform(-0.0001,0.0001)  #this wiggle solves a later indexing ambiguity for corner tracts\n",
    "    wedgeAngle[nWedges-1] = 2.*pi - (np.sum(wedgeAngle) - wedgeAngle[nWedges-1] ) #squaring up to 2pi total\n",
    "    startAngle = [angle0[t] for nW in range(nWedges)]\n",
    "    for nW in range(1,nWedges):\n",
    "        startAngle[nW] = startAngle[nW-1] + wedgeAngle[nW-1]\n",
    "    endAngle = [startAngle[nW] + wedgeAngle[nW] for nW in range(nWedges)]\n",
    "    #  TRIAL LOOP TO SEE WHICH WEDGES CAN FILL TO TARGET POP w/equiangle wedges\n",
    "    maxWedgePoly = [ buildWedge(hdCP[t],startAngle[nW],endAngle[nW], maxD, xScale) for nW in range(nWedges) ]    \n",
    "    maxWedgePop =[ hdCPpop[t]*wedgeAngle[nW]/(2.*pi) for nW in range(nWedges) ]  #seed wedge with fraction of its home tract pop\n",
    "    willFill = [0] * nWedges #would this wedge meet its target with infinite radius?\n",
    "    for nW in range(nWedges):   #... then add in-county Pop and wedge Pop from contiguous chain of counties\n",
    "        iCP, Li   = getCountyWP(t,maxWedgePoly[nW], hdCP, hdCPpop, countyHDlist[hC])\n",
    "        #nonCP, Ln = getNonCWP(maxWedgePoly[nW], hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyList) \n",
    "        nonCP, Ln = getNonCWP_c(startAngle[nW],endAngle[nW], hC, hdCP, hdCPpop, countyGeom, countyPop, countyHDlist,\n",
    "                                opt2nbrCtyList, uuDist[t], uuAngle[t], maxWedgePoly[nW])\n",
    "        maxWedgePop[nW] += (iCP + nonCP)\n",
    "        wedgeList[nW] = Li + Ln\n",
    "        if maxWedgePop[nW] > targetWedgePop[nW]:\n",
    "            willFill[nW] = 1\n",
    "     \n",
    "    if np.sum(willFill) < nWedges:  #at least one wedge couldn't reach its wedgePop target (went over boundary) ...\n",
    "        minW = maxWedgePop.index(np.min(maxWedgePop)) #.. so we will orient the 0th wedge to face the shortest wedgePop's closest boundary\n",
    "        exitAngle = getExitAngle(hdCP[t],maxWedgePoly[minW], MAPhull, startAngle[minW], endAngle[minW])\n",
    "        angle0[t] = exitAngle - 0.5*(2.*pi / nWedges)  #Now reset all angles based on new starting orientation.  All wedge angles still equal\n",
    "        startAngle = [angle0[t] for nW in range(nWedges)]\n",
    "        for nW in range(1,nWedges):\n",
    "            startAngle[nW] = startAngle[nW-1] + wedgeAngle[nW-1]\n",
    "        endAngle = [startAngle[nW] + wedgeAngle[nW] for nW in range(nWedges)]\n",
    "        maxWedgePoly = [buildWedge(hdCP[t],startAngle[nW],endAngle[nW], maxD, xScale) for nW in range(nWedges) ]\n",
    "        \n",
    "        willFill = [0]*nWedges\n",
    "        #Now re-calc each maxWedgePop if we extend wedge's radius past map with new angle0 orientation (wedge angles still constant)\n",
    "        maxWedgePop =[ hdCPpop[t]*wedgeAngle[nW]/(2.*pi) for nW in range(nWedges) ]  #seed wedge with fraction of its home tract pop        \n",
    "        for nW in range(nWedges):   #... then add in-county and nonCounty wedge Pop from contiguous chain of counties\n",
    "            iCP, Li   = getCountyWP(t,maxWedgePoly[nW], hdCP, hdCPpop, countyHDlist[hC])\n",
    "            #nonCP, Ln = getNonCWP(maxWedgePoly[nW], hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyList)\n",
    "            nonCP, Ln = getNonCWP_c(startAngle[nW],endAngle[nW], hC, hdCP, hdCPpop, countyGeom, countyPop, countyHDlist,\n",
    "                                    opt2nbrCtyList, uuDist[t], uuAngle[t], maxWedgePoly[nW])\n",
    "            maxWedgePop[nW] += (iCP + nonCP)\n",
    "            wedgeList[nW] = Li + Ln\n",
    "            if maxWedgePop[nW] > targetWedgePop[nW]:\n",
    "                willFill[nW] = 1       \n",
    "    \n",
    "    if np.sum(willFill) < nWedges:  #check if we need to modify wedge angles after possible re-orientation.  \n",
    "        # If so, re-draw maxWedgePoly's, re-calc maxWedgePops\n",
    "        nUnfilledWedges = nWedges - np.sum(willFill)\n",
    "        isChange, newInclA = getNewAngles(maxWedgePop, targetWedgePop, aDP, levelL, minAdjRatio, maxAngle, maxAngleRatio, nUnfilledWedges )\n",
    "        if isChange: #no longer equi-angle\n",
    "            newStartAngle = [0.5*(startAngle[nW]+endAngle[nW]) - 0.5*newInclA[nW] for nW in range(nWedges) ]\n",
    "            newEndAngle =   [0.5*(startAngle[nW]+endAngle[nW]) + 0.5*newInclA[nW] for nW in range(nWedges) ]\n",
    "            startAngle, endAngle, wedgeAngle = newStartAngle.copy(), newEndAngle.copy(), newInclA.copy()\n",
    "            maxWedgePoly = [ buildWedge(hdCP[t],startAngle[nW],endAngle[nW], \n",
    "                                        maxD/math.cos(0.5*wedgeAngle[nW]), xScale ) for nW in range(nWedges) ]\n",
    "            willFill = [0]*nWedges\n",
    "            #Now re-calc each maxWedgePop if we extend wedge's radius past map with new angle0 orientation and new wedge angles\n",
    "            maxWedgePop =[ hdCPpop[t]*wedgeAngle[nW]/(2.*pi) for nW in range(nWedges) ]  #seed wedge with fraction of its home tract pop\n",
    "            for nW in range(nWedges):   #... then add in-county Pop and wedge Pop from contiguous chain of counties\n",
    "                iCP, Li   = getCountyWP(t,maxWedgePoly[nW], hdCP, hdCPpop, countyHDlist[hC])                \n",
    "                #nonCP, Ln = getNonCWP(maxWedgePoly[nW], hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyList)\n",
    "                nonCP, Ln = getNonCWP_c(startAngle[nW],endAngle[nW], hC, hdCP, hdCPpop, countyGeom, countyPop, countyHDlist,\n",
    "                                        opt2nbrCtyList, uuDist[t], uuAngle[t], maxWedgePoly[nW])\n",
    "                maxWedgePop[nW] += (iCP + nonCP)\n",
    "                wedgeList[nW] = Li + Ln\n",
    "            minW = wedgeAngle.index(np.max(wedgeAngle)) #should be 0th wedge, but playing it safe.  This is the 1st wide-angle wedge ..\n",
    "            oppW = int(int(minW+nWedges/2)%nWedges)   #and its opposite\n",
    "            if maxWedgePop[minW] > maxWedgePop[oppW] and maxWedgePop[oppW] < aDP / nWedges:  #minW and oppW are flipped after inclA adjmt\n",
    "                oppW = minW\n",
    "                minW = int(int(minW+nWedges/2)%nWedges)\n",
    "            if maxWedgePop[minW] < targetWedgePop[oppW]:  #we need to constrain oppW in this HD2 implementation; redistribute tgt to adjacents\n",
    "                maxNonOppW = np.sum(maxWedgePop) - maxWedgePop[oppW] #...but only if other wedges can pick up slack; need to check\n",
    "                minOppWedgePop = aDP - maxNonOppW  #cannot set oppW target below this or we won't reach aDP across all wedges\n",
    "                barredList = [oppW]\n",
    "                targetWedgePop[oppW] = max(minOppWedgePop, maxWedgePop[minW] + oppWt * (targetWedgePop[oppW] - maxWedgePop[minW]) )\n",
    "                tWPgap = aDP / float(nWedges) - targetWedgePop[oppW] \n",
    "                for nW in range(nWedges):\n",
    "                    if nW != minW and nW != oppW:\n",
    "                        targetWedgePop[nW] += tWPgap/float(nWedges - 2.)  #if oppW target is limited, allot to adjacent wedges\n",
    "            for nW in range(nWedges):\n",
    "                if maxWedgePop[nW] > targetWedgePop[nW]:\n",
    "                    willFill[nW] = 1  \n",
    "    \n",
    "    if abs(np.sum(targetWedgePop) / aDP - 1.) > 0.001:\n",
    "        raise Exception(\"FAIL! Our target wedgepops\",targetWedgePop, np.sum(targetWedgePop),\"no longer add up to\",aDP)\n",
    "    \n",
    "    if np.sum(willFill) == nWedges:  #all wedges will fill.  Will any leave a small near-boundary remnant?  If so, pick up smallest remnant\n",
    "        remnantWedgePopFrac = [ ( maxWedgePop[w] - targetWedgePop[w] )/targetWedgePop[w] for w in range(nWedges) ]\n",
    "        if np.min(remnantWedgePopFrac) < maxUncap :  #lessen tWP's of *adjacent* wedges, then increase this wedge's target --> max\n",
    "            minW = remnantWedgePopFrac.index(np.min(remnantWedgePopFrac))\n",
    "            oppW = int((minW+nWedges/2)%nWedges)\n",
    "            #print(\"filling to boundary for tract,wedge, tWP, mWP =\",t,minW, r3(targetWedgePop[minW]), maxWedgePop[minW])\n",
    "            for nW in range(nWedges):\n",
    "                if nW != minW and nW != oppW:\n",
    "                    targetWedgePop[nW] -= (remnantWedgePopFrac[minW] * targetWedgePop[minW] ) / (nWedges - 2.)\n",
    "            targetWedgePop[minW] = maxWedgePop[minW]\n",
    "            #       OK, READY TO SOLVE FOR NON-FILLED WEDGE SIZES once we adjust targets for unfilled wedges\n",
    "    #print(t,\" prior to rebalanceTWP call, mWPs, tWPs are\",maxWedgePop, targetWedgePop)\n",
    "    targetWedgePop, willFill = rebalanceTWPs(maxWedgePop, targetWedgePop, barredList)\n",
    "    #if np.max(targetWedgePop) - np.min(targetWedgePop) > 0.02 * aDP: #debug\n",
    "    #    print(\"for tract\",t,\",  After rebalancing but before tweaks for blocky pop adds: willFill, targetWedgePops and maxWedgePops are ...\")\n",
    "    #    for w in range(nWedges):\n",
    "    #        print(w, willFill[w],r3(targetWedgePop[w]),int(maxWedgePop[w]) )\n",
    "    for w in range(nWedges):  #WHEW!  WE CAN FINALLY ASSIGN ALL WEDGES' POPS AND TRACTLISTS\n",
    "        loop = 0\n",
    "        if willFill[w] == 0:  #wedge is maxed out\n",
    "            wedgePop[w] = maxWedgePop[w]\n",
    "            #wedgeList[w] = ...  #we already captured this list = maxWedge list\n",
    "            HDradius[t][w] = maxD/math.cos(0.5*wedgeAngle[w])\n",
    "        else:  #need to solve for wedge radius to meet targetPop.  Use bisection as scipy minimize no faster\n",
    "            HDcpWP = hdCPpop[t] * wedgeAngle[w]/(2.*pi)\n",
    "            nonHDcpTWP = targetWedgePop[w] - HDcpWP\n",
    "            #wedgePop[w], wedgeList[w], HDradius[t][w] = solveWedgeB(nontractTWP,t,hC,maxWedgePoly[w],tolerPop,tractCP, tractPop,\n",
    "            #                                                        countyNo,countyTractList,countyGeom, neighborCountyList,uuDist[t])\n",
    "            wedgePop[w], wedgeList[w], HDradius[t][w] = solveWedgeC(nonHDcpTWP,t,hC, maxWedgePoly[w],startAngle[w], endAngle[w], tolerPop,\n",
    "                                                                    hdCP, hdCPpop,HDcountyNo, countyHDlist,countyGeom,\n",
    "                                                                    opt2nbrCtyList,uuDist[t],uuAngle[t])\n",
    "            popGap = nonHDcpTWP - wedgePop[w]  #gap between target and solved wedge pop; can be negative\n",
    "            notYetAdjusted, nextW = True, w+1  #looking to adjust a later wedge's target pop to minimize drift in total HD pop\n",
    "            while notYetAdjusted and nextW < nWedges:\n",
    "                if willFill[nextW] == 1 and maxWedgePop[nextW] > targetWedgePop[nextW] + popGap :  #can accommodate\n",
    "                    targetWedgePop[nextW] += popGap\n",
    "                    notYetAdjusted = False\n",
    "                nextW +=1          \n",
    "\n",
    "        HDangle[t][w] = startAngle[w]\n",
    "    #print(t,\"tract. After TWP adjustment, targetWedgePops are\",targetWedgePop)\n",
    "    HDtractList[t] = [t]\n",
    "    totPop = hdCPpop[t]\n",
    "    for nW in range(nWedges):\n",
    "        for tt in wedgeList[nW]:\n",
    "            HDtractList[t].append(tt)  #building the list of tracts in the Home District  (we'll keep up with below changes)\n",
    "            totPop += hdCPpop[tt]\n",
    "    offsetPop = totPop - aDP  #we have solved for all wedge radii to get each within one tractPop of target ... \n",
    "    HDvPop[t] = totPop\n",
    "    #if offsetPop > 0:   #... now include a splitPoly to nail the avg District Pop\n",
    "    #    isOver = True  #we slightly overshot.  ID the farthest-away tract for split-jettison\n",
    "    #    splitTractNo[t], splitTractUse[t] = getPartialTract(t, HDtractList[t], offsetPop, uuDist[t], hdCPpop, neighborList)\n",
    "    #    HDvPop[t] = totPop - (1. - splitTractUse[t]) * tractPop[splitTractNo[t]]\n",
    "    #if offsetPop < 0:\n",
    "    #    isOver = False  #we have undershot.  Pick up the nearest contiguous tract that can be split to fill the gap\n",
    "    #    splitTractNo[t], splitTractUse[t] = getPartialTract(t, HDtractList[t], offsetPop, uuDist[t], tractPop, neighborList)\n",
    "    #    HDtractList[t].append(splitTractNo[t])\n",
    "    #    HDvPop[t] = totPop + splitTractUse[t]*tractPop[splitTractNo[t]]       \n",
    "    #if abs(1. - HDvPop[t]/aDP) > 0.005 :  #something went wrong with pop assignation for this HD\n",
    "    #    print(\"WARNING! Total Home District pop was\",HDvPop[t],\"vs target\",aDP,\"for tract\",t)   ##### hdCP topology not yet known; skip partial\n",
    "        \n",
    "    HDPoly1[t] = dummyPoly  #tractGeom[t] #skip constructing the HD poly shape.  Do compute area of the Home District, including final partial\n",
    "    HDarea[t] = 0.\n",
    "    for tt in HDtractList[t]:\n",
    "        if tt == splitTractNo[t]:\n",
    "            tractUse[tt] += nDistricts * HDweight[t] * splitTractUse[t] \n",
    "            #HDarea[t]   += tractArea[tt] * splitTractUse[t]  #these are original (nonsquished) areas\n",
    "            \n",
    "        else:\n",
    "            tractUse[tt] += nDistricts * HDweight[t]\n",
    "            #HDarea[t]    += tractArea[tt]\n",
    "            #HDPoly1[t] = HDPoly1[t].union(tractGeom[tt])\n",
    "    HDPoly1[t] = buildPoly(hdCP[t],HDradius[t], HDangle[t] )\n",
    "    #HDarea[t] = HDPoly1[t].area + splitTractUse[t] * tractArea[splitTractNo[t]]  \n",
    "    #if splitTractUse[t] > 0.5:\n",
    "    #    HDPoly1[t] = HDPoly1[t].union(tractGeom[splitTractNo[t]])\n",
    "                          \n",
    "    #ALL DONE ESTABLISHING THE FINAL HDTRACTLIST.  FINALIZE STATS\n",
    "totalTime = time.time() - codeStartTime\n",
    "print(r3(totalTime),\"seconds elapsed. All done computing HD shapes and tractlists.  Here is a histogram of vtd usage.\")\n",
    "n_bins=50\n",
    "popTractUse, plotWts = [tractUse[t] for t in populatedTractList], [HDweight[t] for t in populatedTractList]\n",
    "\n",
    "origHDuseAvg, origHDuseSD = getWeightedAvgAndSD(tractUse,HDweight)\n",
    "print(\"vtd avg and sd usage are\",r5(origHDuseAvg), r5(origHDuseSD) )\n",
    "\n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "ax.hist(popTractUse, bins=n_bins, weights=plotWts)\n",
    "plt.show()\n",
    "HDvPop = [np.sum([hdCPpop[tt] for tt in HDtractList[t]]) for t in range(nHDs)]\n",
    "plt.scatter([hdCPpop[t] for t in populatedTractList],[HDvPop[t] for t in populatedTractList] )\n",
    "print(\"here are your HD pops\")\n",
    "plt.show()\n",
    "origHDHDtractList = [HDtractList[t].copy() for t in range(nHDs)] #save for posterity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "b7f36a0f-a3c6-4b07-aecd-9e010b02918f",
   "metadata": {},
   "outputs": [],
   "source": [
    "DATE = \"27May\"  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "37c238bb-b340-431b-ad11-95e4409d9699",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now we will write the polygon-based results to a file\n"
     ]
    }
   ],
   "source": [
    "#last block of option 2 (i.e. generating polygonal HDs from scratch)\n",
    "print(\"Now we will write the polygon-based results to a file\")\n",
    "tractNo = [t for t in range(nHDs) ]\n",
    "HDangle0 = [HDangle[t][0] for t in range(nHDs) ]\n",
    "HDangle1 = [HDangle[t][1] for t in range(nHDs) ]\n",
    "HDangle2 = [HDangle[t][2] for t in range(nHDs) ]\n",
    "HDangle3 = [HDangle[t][3] for t in range(nHDs) ]\n",
    "HDradius0 = [HDradius[t][0] for t in range(nHDs)]\n",
    "HDradius1 = [HDradius[t][1] for t in range(nHDs)]\n",
    "HDradius2 = [HDradius[t][2] for t in range(nHDs)]\n",
    "HDradius3 = [HDradius[t][3] for t in range(nHDs)]\n",
    "hdCPx, hdCPy =   [hdCP[t].x for t in range(nHDs)], [hdCP[t].y for t in range(nHDs)]\n",
    "\n",
    "paramList = [\"STATE\",\"statePop\",\"nDistricts\",\"nHDs\",\"nWedges\",\"popn-toler\",\"levelL\", \"maxAngleRatio\",\n",
    "             \"maxAngle\",\"minAdjRatio\",\"maxUncap\", \"oppWt\", \"calc sec\",\"xScale\",\"outputs...\"]\n",
    "paramValues = [STATE,statePop, nDistricts, nHDs, nWedges, tolerPop, levelL, maxAngleRatio, maxAngle, minAdjRatio, maxUncap,\n",
    "               oppWt, totalTime, xScale, -777]\n",
    "for i in range(nHDs-len(paramList)):\n",
    "    paramList.append(\".\")\n",
    "    paramValues.append(-99)  #so all columns have same number of entries, even the parameter list\n",
    "HDdf = pd.DataFrame( {\"paramList\": paramList,\"paramValues\":paramValues,\"countyNo\":HDcountyNo,\n",
    "                    \"tractNo\":tractNo,\"centroid x\":hdCPx,\"centroid y\":hdCPy,\"tractPop\":hdCPpop,\n",
    "                    \"HDweight\":HDweight,\"HD-pop\":HDvPop,\"HDarea\":HDarea, \"countyNo\":countyNo,\n",
    "                    \"startAngle\":angle0,\"HDangle0\":HDangle0,\"HDangle1\":HDangle1,\"HDangle2\":HDangle2,\"HDangle3\":HDangle3,\n",
    "                    \"HDradius0\":HDradius0,\"HDradius1\":HDradius1,\"HDradius2\":HDradius2, \"HDradius3\":HDradius3,\"tractUse\":tractUse,\n",
    "                    \"splitTractNo\":splitTractNo,\"splitTractUse\":splitTractUse,\"HDtractList\":HDtractList} ) \n",
    "\n",
    "#outname = STATE+str(int(nTracts))+\"HD2Bnopatch\"+str(int(nDistricts))+\"nW4.csv\"  #solveWedgeB\n",
    "outname = STATE+str(int(nHDs))+\"convexHD2_\"+str(int(nDistricts))+\"nW4_\"+DATE+\".csv\"  #solveWedgeC\n",
    "#outname = STATE+str(int(nTracts))+\"HD2Buutpatch\"+str(int(nDistricts))+\"nW4.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "HDdf.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "075013a3-f3ee-4a44-ac4a-27a7492e027a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "./2024state_HD_output/IL10084convexHD2_17nW4_27May.csv\n"
     ]
    }
   ],
   "source": [
    "print(\"./\"+outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "6e7e8ccd-8e11-4d6d-970d-b059401e0a3b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the original HD polygon shape assignment csv, e.g. ./2024state_HD_output/FL7211convexHD2_26nW4_03Mar.csv or ./state_HD_output/AZ9HD1tol0.005nW425Mar.csv ./2024state_HD_output/IL10084convexHD2_17nW4_27May.csv\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I have read back in the original HD shapes\n",
      "Ready to capture unit centroids based on these HD poly shapes; see next block\n"
     ]
    }
   ],
   "source": [
    "#OPTION 2 --> 1 - we already have an ensemble of HDpoly's and their weights (from running option 2 above)\n",
    "#read them in\n",
    "#determine each cluster's required area fraction capture to get 1.00 cluster use across the HD set\n",
    "#then determine total pop (including cluster in/out) for each HD, and total unit use\n",
    "#then move into triage\n",
    "infilename = input(\"enter the original HD polygon shape assignment csv, \"+ \n",
    "                   \"e.g. ./2024state_HD_output/FL7211convexHD2_26nW4_03Mar.csv or ./state_HD_output/AZ9HD1tol0.005nW425Mar.csv\")\n",
    "shapeDF = pd.read_csv(infilename)\n",
    "HDvPop = shapeDF[\"HD-pop\"].to_list()\n",
    "HDweight = shapeDF['HDweight'].to_list() #shapeDF['HDwt'].to_list() or #shapeDF['HDweight'].to_list()\n",
    "HDarea = shapeDF['HDarea'].to_list()\n",
    "#tractPop = shapeDF['tractPop'].to_list()   #we will use vtd-mapped pops instead\n",
    "nHDs = len(shapeDF)\n",
    "hdCPx = shapeDF['centroid x'].to_list()   #note: these may be translated from outcroppings into a convex representation of the map\n",
    "hdCPy = shapeDF['centroid y'].to_list()\n",
    "hdCP = [Point(hdCPx[t], hdCPy[t]) for t in range(nHDs) ]\n",
    "HDradius0 = shapeDF['HDradius0'].to_list()\n",
    "HDradius1 = shapeDF['HDradius1'].to_list()\n",
    "HDradius2 = shapeDF['HDradius2'].to_list()\n",
    "HDradius3 = shapeDF['HDradius3'].to_list()\n",
    "HDangle0 = shapeDF['HDangle0'].to_list()\n",
    "HDangle1 = shapeDF['HDangle1'].to_list()\n",
    "HDangle2 = shapeDF['HDangle2'].to_list()\n",
    "HDangle3 = shapeDF['HDangle3'].to_list()\n",
    "HDradius, HDangle = list(), list()\n",
    "for t in range(nHDs):\n",
    "    HDradius.append( [HDradius0[t],HDradius1[t],HDradius2[t],HDradius3[t] ] )\n",
    "    HDangle.append(  [HDangle0[t], HDangle1[t], HDangle2[t], HDangle3[t]  ] )\n",
    "print(\"I have read back in the original HD shapes\")\n",
    "popHDlist = list()\n",
    "HDpoly = [dummyPoly for t in range(nHDs)]\n",
    "for t in range(nHDs):\n",
    "    if HDweight[t] > 0.000001:\n",
    "        popHDlist.append(t)\n",
    "        HDpoly[t] = buildArcPoly(hdCP[t],HDradius[t], HDangle[t], xScale)\n",
    "if \"countyNo\" in shapeDF.columns.values:  #\"pigs\" == \"can fly\":\n",
    "    HDcountyNo = shapeDF['countyNo'].to_list()\n",
    "else:\n",
    "    print(\"County numbers not in input file. Now I will assign each HD center to a county based on the county geoms\")\n",
    "    HDcountyNo = [-999]*nHDs\n",
    "    for t in popHDlist:\n",
    "        for c, geom in enumerate(countyGeom):\n",
    "            if geom.contains(hdCP[t]):\n",
    "                HDcountyNo[t] = c\n",
    "                break\n",
    "    unassignedList = list()\n",
    "    for t in popHDlist:\n",
    "        if HDcountyNo[t] == -999:\n",
    "            unassignedList.append(t)\n",
    "    if len(unassignedList) > 0:\n",
    "        print(\"I found\",len(unassignedList),\"populd HDs whose centers fall outside vtd-based county lines.  Assign to closest county\")\n",
    "        for t in unassignedList:\n",
    "            minDist = maxD\n",
    "            for c in range(nCounties):\n",
    "                dist = countyGeom[c].distance(hdCP[t])\n",
    "                if dist < minDist:\n",
    "                    minDist = dist\n",
    "                    HDcountyNo[t] = c\n",
    "    if len(unassignedList) > 0:\n",
    "        if len(unassignedList) > 20:\n",
    "            print(\"  (too many to plot individually)\")\n",
    "        else:\n",
    "            print(\"FYI, here are those manually assigned HDcenters to their counties\")\n",
    "            for t in unassignedList:\n",
    "                print(t,HDweight[t],\" is the HD row and its weight in the ensemble\")\n",
    "                plotPoly(hdCP[t].buffer(0.1))\n",
    "                plotCenter(int(HDvPop[t]),hdCP[t],6)\n",
    "                plotPoly(countyGeom[HDcountyNo[t]])\n",
    "                plotPoly(MAP,0.2)\n",
    "                plt.show()\n",
    "print(\"Ready to capture unit centroids based on these HD poly shapes; see next block\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "3f0f8434-5f7a-41d1-bd86-07ec230b4aef",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now, let me renormalize the HDweights if there were cut districts\n",
      "our HDweight sum was 0.9999999999997946 but is now 1.0\n"
     ]
    }
   ],
   "source": [
    "print(\"now, let me renormalize the HDweights if there were cut districts\")\n",
    "sumWt = np.sum(HDweight)\n",
    "HDweight = [HDweight[t]/sumWt for t in range(nHDs) ]\n",
    "\n",
    "print(\"our HDweight sum was\",sumWt,\"but is now\",np.sum(HDweight))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "af22eba0-8e05-43e7-b96b-6aedab016957",
   "metadata": {},
   "outputs": [],
   "source": [
    "#see early states for continuing w/option 1.  NC and later use option 3 ....\n",
    "# ****if this is a cold restart, would need to read in unit topology before below block  **"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "8d5f678f-c2df-4ee7-bafe-fd75ba2cb42e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lead = 'option3' - create HDunitLists based on each HD's tractList, with in-out for multiVTD units\n"
     ]
    }
   ],
   "source": [
    "#OPTION 3 \n",
    "print(\"lead = 'option3' - create HDunitLists based on each HD's tractList, with in-out for multiVTD units\")\n",
    "HDtractListString = shapeDF[\"HDtractList\"]\n",
    "HDtractList = [ast.literal_eval(HDtractListString[t]) for t in range(nHDs)]\n",
    "nCCBs = len(CCBlist)\n",
    "CCBpopFrac = [[0. for j in range(nCCBs) ]  for t in range(nHDs)]\n",
    "\n",
    "unitParentVTDno = [-999 for u in range(nUnits)]\n",
    "for u in range(nUnits):    \n",
    "    if allUnits[u] %1 == 0:\n",
    "        v = allUnits[u]\n",
    "        unitParentVTDno[u] = parentVTDno[v]\n",
    "              "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "ec034144-b3dc-4b72-9350-6d85cabcb8a2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing option3, now assigning each HD's units (excluding CCB's) based on the captured whole vtd's\n",
      "working on vtd --> unit conversion for HD 1 last HD had pop 754971.973\n",
      "working on vtd --> unit conversion for HD 1001 last HD had pop 724324.0\n",
      "working on vtd --> unit conversion for HD 2001 last HD had pop 754235.0\n",
      "working on vtd --> unit conversion for HD 3001 last HD had pop 688388.0\n",
      "working on vtd --> unit conversion for HD 4001 last HD had pop 754138.0\n",
      "working on vtd --> unit conversion for HD 5001 last HD had pop 753101.0\n",
      "working on vtd --> unit conversion for HD 6001 last HD had pop 752945.0\n",
      "working on vtd --> unit conversion for HD 7001 last HD had pop 753342.0\n",
      "working on vtd --> unit conversion for HD 8001 last HD had pop 754060.0\n",
      "working on vtd --> unit conversion for HD 9001 last HD had pop 743329.247\n",
      "working on vtd --> unit conversion for HD 10001 last HD had pop 590629.043\n"
     ]
    }
   ],
   "source": [
    "print(\"Continuing option3, now assigning each HD's units (excluding CCB's) based on the captured whole vtd's\" )\n",
    "HDunitList = [ list() for t in range(nHDs) ]\n",
    "for t in range(nHDs):\n",
    "    if t %1000 == 1:\n",
    "        print(\"working on vtd --> unit conversion for HD\",t,\"last HD had pop\",r3( np.sum([unitPop[u] for u in HDunitList[t-1]]) ) )\n",
    "    capturedCountyPop = [0. for c in range(nCounties)]\n",
    "    capturedCCBpop = [0. for i in range(nCCBs)]\n",
    "    for v in HDtractList[t]:\n",
    "        c = HDcountyNo[v]\n",
    "        if c in range(nCounties):  #we assigned countyno = -999 to unpopulated tracts\n",
    "            if c in unitCounties:\n",
    "                capturedCountyPop[c] += tractPop[v]\n",
    "            elif c in allFusedCounties:\n",
    "                for i, L in enumerate(CCBlist):\n",
    "                    if c in L:\n",
    "                        capturedCCBpop[i] += tractPop[v]\n",
    "            else:  #this vtd not part of a unit or fused county.  Could be split into fragments\n",
    "                for u in countyUnitList[c]:\n",
    "                    if unitParentVTDno[u] == v :  #we assign all units = vtd fragments from this HDTL-captured vtd\n",
    "                        HDunitList[t].append(u)\n",
    "    for c in unitCounties:\n",
    "        if capturedCountyPop[c] > 0.5 * countyPop[c]:\n",
    "            HDunitList[t].append(allUnits.index(c+0.5))\n",
    "    for i in range(nCCBs):  #don't yet assign in/out CCBs.  We'll do so in below block.  Just update max possible use for each CCB\n",
    "        CCBpopFrac[t][i] = capturedCCBpop[i] / CCBpop[i]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "1494814c-7b90-425c-b8b1-3a2006bdeb2d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing option 3.  Determine each CCB's use if we add it to all adjoining HDs\n",
      "CCBno 0 with pop 211407.0 would be used 1.488 if we added it to all adjoining districts\n",
      "Here is the histogram of relative district pop with these added\n",
      "CCBno 1 with pop 82367.0 would be used 1.423 if we added it to all adjoining districts\n",
      "Here is the histogram of relative district pop with these added\n",
      "CCBno 2 with pop 83357.0 would be used 1.633 if we added it to all adjoining districts\n",
      "Here is the histogram of relative district pop with these added\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 if we are not allowed to use multiple CCB's in a single HD 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CCBno 0 with pop 211407.0 would be used 1.4876626028254354 if we added it to all adjoining districts with no 2-CCB districts\n",
      "CCBno 1 with pop 82367.0 would be used 1.4218625268370761 if we added it to all adjoining districts with no 2-CCB districts\n",
      "CCBno 2 with pop 83357.0 would be used 1.097143822271264 if we added it to all adjoining districts with no 2-CCB districts\n"
     ]
    }
   ],
   "source": [
    "print(\"Continuing option 3.  Determine each CCB's use if we add it to all adjoining HDs\")\n",
    "CCBwouldUse = [0. for i in range(nCCBs)]\n",
    "CCBaddCandidates = [list() for i in range(nCCBs)]\n",
    "for j in range(nCCBs):\n",
    "    jNo = allUnits.index(j+0.25)\n",
    "    ccbNbrSet = set(unitNbrs[jNo])\n",
    "    withCCBpopRat = list()\n",
    "    for t in range(nHDs):\n",
    "        if len(ccbNbrSet.intersection(set(HDunitList[t]))) > 0:\n",
    "            CCBwouldUse[j] += HDweight[t] * nDistricts\n",
    "            CCBaddCandidates[j].append(t)\n",
    "            withCCBpopRat.append((np.sum([unitPop[u] for u in HDunitList[t]]) + CCBpop[j]) / aDP )\n",
    "    print(\"CCBno\",j,\"with pop\",CCBpop[j],\"would be used\",r3(CCBwouldUse[j]),\"if we added it to all adjoining districts\")\n",
    "    print(\"Here is the histogram of relative district pop with these added\")\n",
    "    plt.hist(withCCBpopRat,histtype=\"step\",label=\"CCB \"+str(j))\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "avoidMultiCCBuse = int(input(\"enter 1 if we are not allowed to use multiple CCB's in a single HD\"))  #option by state\n",
    "if avoidMultiCCBuse == 1:\n",
    "    for j in range(nCCBs):  #this block -- preventing HDs from picking up multiple CCB's; instead, pick up the closest one  \n",
    "        jNo = allUnits.index(j+0.25)\n",
    "        for jj in range(j+1, nCCBs):\n",
    "            jjNo = allUnits.index(j+0.25)\n",
    "            for t in CCBaddCandidates[j].copy():\n",
    "                if t in CCBaddCandidates[j]:\n",
    "                    if t in CCBaddCandidates[jj].copy():\n",
    "                        dist_j, dist_jj = hdCP[t].distance(unitCP[jNo]), hdCP[t].distance(unitCP[jjNo])\n",
    "                        if dist_j > dist_jj:\n",
    "                            CCBaddCandidates[j].remove(t)  #for MN, don't allow any districts with two CCB's\n",
    "                            CCBwouldUse[j] -= HDweight[t] * nDistricts\n",
    "                        else:\n",
    "                            CCBaddCandidates[jj].remove(t)\n",
    "                            CCBwouldUse[jj] -= HDweight[t] * nDistricts\n",
    "for j in range(nCCBs):    \n",
    "    print(\"CCBno\",j,\"with pop\",CCBpop[j],\"would be used\",CCBwouldUse[j],\"if we added it to all adjoining districts with no 2-CCB districts\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "0d38eb0e-b516-4fd4-bb9e-6ca0eecfa772",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing option 3. Now assign CCB units.  For each, work from most to least underpopped\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter target CCBuse for CCB 0 I reco 1.02, as we may lose a little later 1.01\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final unit use of CCB 0 is 1.01093 ; here is a histogram of HDpop using this CCB\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter target CCBuse for CCB 1 I reco 1.02, as we may lose a little later 1.03\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final unit use of CCB 1 is 1.03027 ; here is a histogram of HDpop using this CCB\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter target CCBuse for CCB 2 I reco 1.02, as we may lose a little later 1.03\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final unit use of CCB 2 is 1.03117 ; here is a histogram of HDpop using this CCB\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Continuing option 3. Now assign CCB units.  For each, work from most to least underpopped\")\n",
    "#previously, we went from most-used to least-used CCB vtds until each has unit use\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "CCBuse = [0. for i in range(nCCBs)]\n",
    "for j in range(nCCBs):\n",
    "    minCCBuse = float(input(\"enter target CCBuse for CCB \"+str(j)+\" I reco 1.02, as we may lose a little later\"))\n",
    "    postCCBaddPops = list()\n",
    "    unitNo = allUnits.index(j+0.25)\n",
    "    #ccbNbrSet = set(unitNbrs[unitNo])\n",
    "    #ccbFrac = [-1.*CCBpopFrac[t][j] for t in range(nHDs) ]  # -1 to go from most- to least-used\n",
    "    #idx = np.argsort(ccbFrac)\n",
    "    preCCBpop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in CCBaddCandidates[j]]\n",
    "    idx = np.argsort(preCCBpop)\n",
    "    i = 0\n",
    "    t = CCBaddCandidates[j][idx[i]] #idx[i]\n",
    "    while CCBuse[j] < minCCBuse  and i < len(CCBaddCandidates[j]) :  #and CCBpopFrac[t][j] > 0:\n",
    "        t = CCBaddCandidates[j][idx[i]] #idx[i]\n",
    "        CCBuse[j] += HDweight[t] * nDistricts\n",
    "        HDunitList[t].append(unitNo)\n",
    "        postCCBaddPops.append(np.sum([unitPop[u] for u in HDunitList[t] ]))\n",
    "        i +=1\n",
    "    unitUse[unitNo] = CCBuse[j]\n",
    "    print(\"final unit use of CCB\",j, \"is\",r5(CCBuse[j]),\"; here is a histogram of HDpop using this CCB\")\n",
    "    plt.hist(postCCBaddPops)\n",
    "    plt.axvline(aDP,ls=\"--\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf747d9c-cf6d-420e-9c3c-6723619586ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "#end of preliminaries for \"option 3\" - converting HDtractlists to unit lists instead of option 2's geometric probing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "26102ca2-79c1-48db-b873-7fa3a1553911",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "dc26d08c-a5d9-4e7e-9da5-ae98cf658a3a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here is the histogram of HD pops relative to aDP\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "orig unit avg and sd usage are 1.0042 0.10371\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t]]) for t in range(nHDs) ]\n",
    "print(\"Here is the histogram of HD pops relative to aDP\")\n",
    "plt.hist([HDvPop[t] / aDP for t in range(nHDs) ], bins=20, weights = HDweight, label= \"HDpop / target\" )\n",
    "plt.show()\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse, bins=50, weights=unitPop,label=\"read-in\",histtype=\"step\")\n",
    "plt.legend()\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "print(\"orig unit avg and sd usage are\",r5(unpatchedAvg), r5(unpatchedSD) )\n",
    "plt.show()\n",
    "currAvg, currSD = unpatchedAvg, unpatchedSD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "53e4c298-e6cb-4fee-a511-b8f6c3940539",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "c4183011-724a-4014-8c94-f9f9382c7e75",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Did I grossly overuse any units, or skip any live ones?\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "above: underused < 0.5; below overused > 1.6\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Did I grossly overuse any units, or skip any live ones?\")\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < 0.5 and unitPop[u] > 5:\n",
    "        plotPoly(unitGeom[u])\n",
    "        #print(u,unitPop[u], unitUse[u])\n",
    "        #for c in range(nCounties):\n",
    "        #    if u in countyUnitList[c]:\n",
    "        #        print(u,\"is in county\",c)\n",
    "        #        print(\"its neighbor units are\",unitNbrs[u])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()\n",
    "print(\"above: underused < 0.5; below overused > 1.6\")\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 1.6:\n",
    "        plotPoly(unitGeom[u],0.3)\n",
    "plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "ce9292b0-7d6a-419a-9491-d0def779ad04",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are a total of 10082 populated HDs out of 10084\n"
     ]
    }
   ],
   "source": [
    "popHDlist = list()\n",
    "for t in range(nHDs):\n",
    "    if len(HDunitList[t]) > 0:\n",
    "        popHDlist.append(t)\n",
    "populatedTractList = popHDlist.copy()\n",
    "print(\"there are a total of\",len(populatedTractList),\"populated HDs out of\",nHDs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "f7f36559-7f1d-4203-8b24-0e8cc2ce1753",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this will show if we had any duplicated units in HDunitLists\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"this will show if we had any duplicated units in HDunitLists\")\n",
    "excess = [0 for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    excess[t] = len(HDunitList[t]) - len(set(HDunitList[t]))\n",
    "plt.hist(excess)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "27bc7f0a-d7ff-4c68-830f-29ba5013c314",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#popHDlist = populatedTractList.copy()  #somehow our popHDlist started to include the cut District HD starters\n",
    "HDunitList = [list(set(HDunitList[t])) for t in range(nHDs)]\n",
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t]]) for t in range(nHDs)]\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "af8a4945-40c2-40df-8dd4-d516f4de2f0f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "quick classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 700 time is now 101\n",
      "working on HD 1400 time is now 235\n",
      "working on HD 2100 time is now 377\n",
      "working on HD 2800 time is now 493\n",
      "working on HD 3500 time is now 616\n",
      "working on HD 4200 time is now 716\n",
      "working on HD 4902 time is now 778\n",
      "working on HD 5602 time is now 869\n",
      "working on HD 6302 time is now 951\n",
      "working on HD 7002 time is now 1046\n",
      "working on HD 7702 time is now 1137\n",
      "working on HD 8402 time is now 1259\n",
      "working on HD 9102 time is now 1404\n",
      "working on HD 9802 time is now 1535\n",
      "out of 10082 total HDs, there were 6889.0 contiguous and 1415.0 complement-contiguous HDs\n",
      "2784 HDs had both discontiguity problems, while enclave-only = 5883 and discontig only= 409\n",
      "here are the histograms of the small piece and enclave list lengths, total no = 3193 5883\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And here are the small-HD-piece and small-enclave pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### THIS IS THE \"FIND DISCO\" CODE\n",
    "print(\"quick classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "\n",
    "print(\"here are the histograms of the small piece and enclave list lengths, total no =\",\n",
    "      len(smallPieceLists),len(enclaveLists) )\n",
    "plt.hist([s for s in smallPieceLengths],label=\"small piece l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.hist([e for e in enclaveLengths],label=\"enclave l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.legend()\n",
    "plt.show()\n",
    "print(\"And here are the small-HD-piece and small-enclave pops\")\n",
    "plt.hist([sum(unitPop[u] for u in s) for s in smallPieceLists],label=\"small piece 1 pop\",histtype='step')\n",
    "plt.hist([sum(unitPop[u] for u in e) for e in enclaveLists],label=\"enclave 1 pop\",histtype='step')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "40f06e44-45be-4a36-b62c-26698af70e06",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before addressing enclaves, let's triage the discontinuous HDs\n",
      "Now work on dropping smallish disconnected pieces that would keep us above 715993 district pop vs 753676 target\n",
      "we'll also trim any HD with total islands' pop <= 15073\n",
      "working on HD 2\n",
      "working on HD 376\n",
      "working on HD 741\n",
      "working on HD 1206\n",
      "working on HD 1608\n",
      "working on HD 1850\n",
      "working on HD 2251\n",
      "working on HD 2620\n",
      "working on HD 3119\n",
      "working on HD 3527\n",
      "working on HD 4693\n",
      "working on HD 6336\n",
      "working on HD 8136\n",
      "working on HD 8854\n",
      "working on HD 9323\n",
      "working on HD 9693\n",
      "Out of 3193 discontig HDs 3193 had discontig HDs.\n",
      "Of these, 2933 won't be under 715993 after all minor discontigys were shed, while 260 would be too underpopped if we trimmed the discontig pieces\n",
      "here is adjusted pop by original pop for those we trimmed and those we didn't (x)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, reclassify after the trimming\n",
      "reclassifying HD 2\n",
      "reclassifying HD 969\n",
      "reclassifying HD 1850\n",
      "reclassifying HD 2781\n",
      "reclassifying HD 4693\n",
      "reclassifying HD 8590\n",
      "reclassifying HD 9693\n",
      "There are 260 HDs still with both discontinuity problems\n",
      "Additionally, 2609 of the originally discontig HDs are now contig but still have an enclave\n"
     ]
    }
   ],
   "source": [
    "print(\"Before addressing enclaves, let's triage the discontinuous HDs\")\n",
    "#this is the CANTRIM code####\n",
    "\n",
    "#for t in sPgenerator:\n",
    "#    isContig, smallP = isContiguous(filledHDvtdList[t],unitNbrs)\n",
    "#    if isContig:\n",
    "#        print(\"oops!\",t)\n",
    "maxNudgeDownPop = int(0.02 * aDP)\n",
    "minPostFixPop = int(0.95 * aDP)\n",
    "print(\"Now work on dropping smallish disconnected pieces that would keep us above\",minPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "print(\"we'll also trim any HD with total islands' pop <=\",maxNudgeDownPop)\n",
    "nOrigIslands = [0 for t in range(nHDs)]\n",
    "totalIslandPop = [0. for t in range(nHDs)]\n",
    "tryToTrim, canTrim, cantTrim = list(), list(), list()\n",
    "for jj, t in enumerate(sPgenerator):\n",
    "    if jj%200 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    currList, shedList, shedPop = HDunitList[t].copy(), list(),  0.\n",
    "    done,newList = isContiguous(currList,unitNbrs)\n",
    "    if not done:\n",
    "        tryToTrim.append(t)\n",
    "        while not done:\n",
    "            shedList += newList\n",
    "            shedPop += np.sum( [unitPop[u] for u in newList] )\n",
    "            currList = list (  set(currList).difference(set(newList ))  )\n",
    "            done, newList = isContiguous(currList, unitNbrs)\n",
    "            nOrigIslands[t] +=1\n",
    "            \n",
    "        totalIslandPop[t] = shedPop            \n",
    "        if shedPop <= maxNudgeDownPop or HDvPop[t] - shedPop >= minPostFixPop:\n",
    "            canTrim.append(t)\n",
    "            HDvPop[t] -= shedPop\n",
    "            HDunitList[t] = list (set(HDunitList[t]).difference(set(shedList)) )\n",
    "        else:\n",
    "            cantTrim.append(t)\n",
    "print(\"Out of\",len(sPgenerator),\"discontig HDs\",len(tryToTrim),\"had discontig HDs.\")\n",
    "print(\"Of these,\",len(canTrim),\"won't be under\",minPostFixPop,\"after all minor discontigys were shed, while\",\n",
    "      len(cantTrim),\"would be too underpopped if we trimmed the discontig pieces\")\n",
    "plt.scatter([HDvPop[t] + totalIslandPop[t] for t in canTrim],[HDvPop[t] for t in canTrim])\n",
    "plt.scatter([HDvPop[t]                     for t in cantTrim],[HDvPop[t] for t in cantTrim],marker=\"x\")\n",
    "print(\"here is adjusted pop by original pop for those we trimmed and those we didn't (x)\")\n",
    "plt.plot([0.9*aDP, 1.1*aDP],[aDP, aDP], ls=\"--\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Now, reclassify after the trimming\")\n",
    "badDiscoList, stillHasEnclave = list(), list()\n",
    "for i, t in enumerate(sPgenerator):    \n",
    "    if i%500 == 0:\n",
    "        print(\"reclassifying HD\",t)\n",
    "    unbroken, noEnclave, __, ____ = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if not unbroken:\n",
    "        badDiscoList.append(t)  #will do a major triage on these later\n",
    "    if unbroken and not noEnclave:\n",
    "        stillHasEnclave.append(t)\n",
    "print(\"There are\",len(badDiscoList),\"HDs still with both discontinuity problems\")\n",
    "print(\"Additionally,\",len(stillHasEnclave),\"of the originally discontig HDs are now contig but still have an enclave\")\n",
    "eLgenerator += stillHasEnclave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "4037f8cb-661b-4032-bfb9-e147975e3bbb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classify further: ID those with adjoiners intersecting the map boundary vs internal islands\n",
      "working on enclave-generating HD 3 0 seconds elapsed\n",
      "working on enclave-generating HD 1452 5 seconds elapsed\n",
      "working on enclave-generating HD 2997 10 seconds elapsed\n",
      "working on enclave-generating HD 3876 15 seconds elapsed\n",
      "working on enclave-generating HD 4519 19 seconds elapsed\n",
      "working on enclave-generating HD 5264 22 seconds elapsed\n",
      "working on enclave-generating HD 5893 26 seconds elapsed\n",
      "working on enclave-generating HD 6523 30 seconds elapsed\n",
      "working on enclave-generating HD 7129 34 seconds elapsed\n",
      "working on enclave-generating HD 7726 38 seconds elapsed\n",
      "working on enclave-generating HD 8377 43 seconds elapsed\n",
      "working on enclave-generating HD 9161 48 seconds elapsed\n",
      "working on enclave-generating HD 298 53 seconds elapsed\n",
      "working on enclave-generating HD 1533 59 seconds elapsed\n",
      "working on enclave-generating HD 2573 65 seconds elapsed\n",
      "working on enclave-generating HD 4496 71 seconds elapsed\n",
      "working on enclave-generating HD 8856 76 seconds elapsed\n",
      "Out of 8492 HDpolys that generated enclaves, 0 had contiguous adjrs, while 5149 neighbored a state boundary while 3343 had only internal enclaves\n"
     ]
    }
   ],
   "source": [
    "print(\"Classify further: ID those with adjoiners intersecting the map boundary vs internal islands\")\n",
    "internals, edgers, nOK = list(), list(), 0\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(eLgenerator):\n",
    "    if i%500 == 0:\n",
    "        print(\"working on enclave-generating HD\",t,int(time.time()-startTime),\"seconds elapsed\")\n",
    "    twoNbrs = get2nbrs(HDunitList[t],unitNbrs)\n",
    "    isContig, adjSublist = isContiguous(twoNbrs,unitNbrs)\n",
    "    if isContig:\n",
    "        nOK +=1\n",
    "    else:\n",
    "        if len (set(getAdjoiners(HDunitList[t],unitNbrs)).intersection(set(borderUnits)))  > 0:\n",
    "            edgers.append(t)\n",
    "        else:\n",
    "            internals.append(t)\n",
    "print(\"Out of\",len(eLgenerator),\"HDpolys that generated enclaves,\",nOK,\"had contiguous adjrs, while\",len(edgers),\n",
    "      \"neighbored a state boundary while\",len(internals),\"had only internal enclaves\")   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "05f929ce-4f94-47a6-baf4-60c5a89e2ae5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's fill in all enclaves that won't put us over 791360 district pop vs 753676 target\n",
      "working on enclave-y HD 41 . We have evaluated 0 of 8492 enclavy HDs.Time is now 0\n",
      "working on enclave-y HD 3645 . We have evaluated 200 of 8492 enclavy HDs.Time is now 54\n",
      "working on enclave-y HD 4315 . We have evaluated 400 of 8492 enclavy HDs.Time is now 90\n",
      "working on enclave-y HD 5152 . We have evaluated 600 of 8492 enclavy HDs.Time is now 123\n",
      "working on enclave-y HD 5654 . We have evaluated 800 of 8492 enclavy HDs.Time is now 159\n",
      "working on enclave-y HD 6233 . We have evaluated 1000 of 8492 enclavy HDs.Time is now 193\n",
      "working on enclave-y HD 6691 . We have evaluated 1200 of 8492 enclavy HDs.Time is now 228\n",
      "working on enclave-y HD 7140 . We have evaluated 1400 of 8492 enclavy HDs.Time is now 263\n",
      "working on enclave-y HD 7587 . We have evaluated 1600 of 8492 enclavy HDs.Time is now 300\n",
      "working on enclave-y HD 7941 . We have evaluated 1800 of 8492 enclavy HDs.Time is now 339\n",
      "working on enclave-y HD 8204 . We have evaluated 2000 of 8492 enclavy HDs.Time is now 381\n",
      "working on enclave-y HD 8454 . We have evaluated 2200 of 8492 enclavy HDs.Time is now 429\n",
      "working on enclave-y HD 8700 . We have evaluated 2400 of 8492 enclavy HDs.Time is now 470\n",
      "working on enclave-y HD 9275 . We have evaluated 2600 of 8492 enclavy HDs.Time is now 518\n",
      "working on enclave-y HD 1750 . We have evaluated 2800 of 8492 enclavy HDs.Time is now 579\n",
      "working on enclave-y HD 5709 . We have evaluated 3000 of 8492 enclavy HDs.Time is now 634\n",
      "working on enclave-y HD 8578 . We have evaluated 3200 of 8492 enclavy HDs.Time is now 675\n",
      "working on enclave-y HD 220 . We have evaluated 3400 of 8492 enclavy HDs.Time is now 726\n",
      "working on enclave-y HD 929 . We have evaluated 3600 of 8492 enclavy HDs.Time is now 768\n",
      "working on enclave-y HD 1494 . We have evaluated 3800 of 8492 enclavy HDs.Time is now 805\n",
      "working on enclave-y HD 2259 . We have evaluated 4000 of 8492 enclavy HDs.Time is now 845\n",
      "working on enclave-y HD 2939 . We have evaluated 4200 of 8492 enclavy HDs.Time is now 875\n",
      "working on enclave-y HD 3372 . We have evaluated 4400 of 8492 enclavy HDs.Time is now 910\n",
      "working on enclave-y HD 3881 . We have evaluated 4600 of 8492 enclavy HDs.Time is now 943\n",
      "working on enclave-y HD 4387 . We have evaluated 4800 of 8492 enclavy HDs.Time is now 969\n",
      "working on enclave-y HD 4804 . We have evaluated 5000 of 8492 enclavy HDs.Time is now 989\n",
      "working on enclave-y HD 5278 . We have evaluated 5200 of 8492 enclavy HDs.Time is now 1011\n",
      "working on enclave-y HD 5777 . We have evaluated 5400 of 8492 enclavy HDs.Time is now 1036\n",
      "working on enclave-y HD 6221 . We have evaluated 5600 of 8492 enclavy HDs.Time is now 1058\n",
      "working on enclave-y HD 6727 . We have evaluated 5800 of 8492 enclavy HDs.Time is now 1082\n",
      "working on enclave-y HD 7275 . We have evaluated 6000 of 8492 enclavy HDs.Time is now 1106\n",
      "working on enclave-y HD 7807 . We have evaluated 6200 of 8492 enclavy HDs.Time is now 1132\n",
      "working on enclave-y HD 9576 . We have evaluated 6400 of 8492 enclavy HDs.Time is now 1175\n",
      "working on enclave-y HD 15 . We have evaluated 6600 of 8492 enclavy HDs.Time is now 1207\n",
      "working on enclave-y HD 542 . We have evaluated 6800 of 8492 enclavy HDs.Time is now 1250\n",
      "working on enclave-y HD 1181 . We have evaluated 7000 of 8492 enclavy HDs.Time is now 1294\n",
      "working on enclave-y HD 1810 . We have evaluated 7200 of 8492 enclavy HDs.Time is now 1351\n",
      "working on enclave-y HD 2308 . We have evaluated 7400 of 8492 enclavy HDs.Time is now 1403\n",
      "working on enclave-y HD 2916 . We have evaluated 7600 of 8492 enclavy HDs.Time is now 1457\n",
      "working on enclave-y HD 3526 . We have evaluated 7800 of 8492 enclavy HDs.Time is now 1506\n",
      "working on enclave-y HD 6333 . We have evaluated 8000 of 8492 enclavy HDs.Time is now 1538\n",
      "working on enclave-y HD 9323 . We have evaluated 8200 of 8492 enclavy HDs.Time is now 1590\n",
      "working on enclave-y HD 9783 . We have evaluated 8400 of 8492 enclavy HDs.Time is now 1630\n",
      "Out of 8492 HDs with enclaves 8492 had enclaves.\n",
      "Of these, 8380 wouldn't be over 791360 if all enclaves filled, while 112 were too populous\n",
      "here is enclave pop by final pop for those we filled\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### THIS IS THE \"CANFILL\" CODE  #check if sum of enclave pops small enough to add\n",
    "maxNudgeUpPop = int(0.02 * aDP)\n",
    "maxPostFixPop = int(1.05 * aDP)\n",
    "print(\"Now, let's fill in all enclaves that won't put us over\",maxPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "nOrigEnclaves = [0 for t in range(nHDs)]\n",
    "totalEnclavePop = [0. for t in range(nHDs)]\n",
    "tryToFill, canFill, cantFill = list(), list(), list()\n",
    "startTime = time.time()  #takes about xx sec per HD triage\n",
    "        \n",
    "for iii, t in enumerate(internals + edgers):\n",
    "    if iii%200 == 0:\n",
    "        print(\"working on enclave-y HD\",t,\". We have evaluated\",iii,\"of\",len(internals+edgers),\"enclavy HDs.Time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and not noEnclave:  #\"and unbroken\" new 1/15 - discontig HDs will usually appear to have enclaves.  We'll fix these in later block\n",
    "        tryToFill.append(t)\n",
    "        enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "        nOrigEnclaves[t] = len(enclaveLists)\n",
    "        totalEnclavePop[t] = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in enclaveLists ] ) \n",
    "        if HDvPop[t] + totalEnclavePop[t] <= maxPostFixPop or totalEnclavePop[t] < maxNudgeUpPop:\n",
    "            canFill.append(t)\n",
    "            for eL in enclaveLists:\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += np.sum([unitPop[u] for u in eL])\n",
    "        else:\n",
    "            cantFill.append(t)\n",
    "print(\"Out of\",len(internals+edgers),\"HDs with enclaves\",len(tryToFill),\"had enclaves.\")\n",
    "print(\"Of these,\",len(canFill),\"wouldn't be over\",maxPostFixPop,\"if all enclaves filled, while\",len(cantFill),\"were too populous\")\n",
    "plt.scatter([HDvPop[t] for t in canFill],[totalEnclavePop[t] for t in canFill])\n",
    "print(\"here is enclave pop by final pop for those we filled\")\n",
    "plt.show()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "8987ad1f-d372-415d-a2ec-8fc6736c5102",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3343 5149 2784 1900\n",
      "112 112 8380\n"
     ]
    }
   ],
   "source": [
    "print(len(internals),len(edgers),len(doubleTroubleList),len(set(edgers).intersection(set(doubleTroubleList))))\n",
    "print(len(set(edgers).difference(set(canFill))) ,len(cantFill) , len(canFill))\n",
    "#610 3379 2187 1954\n",
    "#80 80 3909  for original MN option3 (assigned CCBs by captured area)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "8fa887be-92e6-422a-8e80-e00fd3265aab",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "defining and displaying current unit use after above manipulations; compare to original farther above.\n",
      "current avg use and its sd are 1.00614 0.10365\n",
      "CCB cluster 0 = unit 9675 with pop 211407.0 now has use of 1.0109291639077487\n",
      "CCB cluster 1 = unit 9676 with pop 82367.0 now has use of 1.0302650347613453\n",
      "CCB cluster 2 = unit 9677 with pop 83357.0 now has use of 1.0851585809742463\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"defining and displaying current unit use after above manipulations; compare to original farther above.\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"= unit\",u,\"with pop\",unitPop[u],\"now has use of\",unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "e9d50ef8-39b2-4e22-a11e-cabeda78721e",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "savedHDunitList = [HDunitList[t].copy() for t in range(nHDs) ]  #safekeeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "b759b3c7-b8a3-4d2c-a8fe-50fa93b3e940",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#savedHDunitList = [HDunitList[t].copy() for t in range(nHDs) ]  #safekeeping\n",
    "HDunitList = [savedHDunitList[t].copy() for t in range(nHDs) ]   #restart\n",
    "HDvPop = [0 for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "plt.axvline(aDP, ls=\"--\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist],bins=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "551454fb-d57c-466f-8b31-39ccb2a728de",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are the HD centers for 112 cantFill HDs with border or big enclaves\n"
     ]
    },
    {
     "data": {
      "image/png": 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SUfQP6Qgkg4TuC0zyIbR/lw5L4a08ma4mlRWGcbyv34JX8f9Asei13Bvyb5Kfk1ge9y6dzx3LRZOvbpHX/fVvF/GF9wEgHoDPTU9wtecxHr647VvwgpVY20Vo1xS7kaipGcT/+SwcF6TjXJVPwfPrcC7LEyetjkCRQRP/H4VTkxIRwjsXv0uRpR/vcQu9pC08pT/I4/qfcUlW/ik9git2KOPnzWP15q0s/PDtFnndmrC4Js8/7nojG/92PkZFnHLriZYPoUMwOMyEjk3GkhFB+Q97KJ+VjfdgNRGTuwU6NOE0SIrUMAus6GchnIr+sX344KovuXFjNnNKB1Hk6oEbBSyQXKMxIcxIJWDdt5PsinzG3nDLab2er7SUzMzNhI75M6orHt3n4JHJb+AwidNtY+KvIXQoxjg79iFxuHeWYYg9clSC0M7UrSGDqoNBJB/CqXu7Tzoz31vPJqMJTfXQb/8BJjr9nSL/c801dI+KJK5LZ3799Ve6du1KSkrKKb1O7h130qsmkcl7hgOQvHcPqutt+MMfWuy9dAQi+RA6FLXKQ/n3uzEm2gkZkRDocITTVD8cUtd00eVTOC1GRebGq/pStTAXz34nNZE2Pkj0scK5nkF5LqrLylizbCkYjCxcuJAePXowderUZr9O8v/+ywcvv9zwfH9qOlG33tqSb6VDEMmH0KF4C2vQKj2EjklGMojrq+1e/VwMPg3EJHPCaVLCTIRf4p+t9ImsA3yxYxc3zf2R6u4D8NhcbAtPYeSGRdSk9SQzM/OUXmNv9UyGj1hERY2GJOn4fCYqXLcRSXgLvpP2T3w7Cx2KubMD24AYKn7aTdmXu/BVuAMdknAa6mer1E9jRVhBOJor4iLAaqfWaEYqK8JYbWZAeRE1aT2RNB/9+s9u9jE9nlL27nsFxbKfkMgi9kbEszcmlvtnPcum4sPX8T2ziZYPoUORJImIq7pjTAql6td9VK8vJGxCJ0LPTkaSRcN9u6M06vMhCC2oX6iNJWcPZE7SU2R+9R/MpZswGyE03klirz1Eho9t9jFNpkjMtZPZsWQF69Lv4qtudVOpdwPb0hJevayF30Q7JmY4FToszeWjcs5enEvzUMLN2AbHYc2IxJhoRxJD3toF164yit/aQvyfhmKItJx4B0E4BbquUlKyiLLSjSgGM9HRowgL63fKxytzlfH22wv4MjwZu1sjvFqjX44ba7rCg/eMacHIg0tzzt8i+RA6PE9uFc4VB6ndUozuVkECJcyMEmHGEGXF0j0Cc2cHSqiYHfVwNRuLUMtd6BqgHVoETK9fDa3REvb1M5DTeFryxiumcWhtkSZrpxxeph+qp1V5cGWWEffgEIzRVgShPal1enjm4cUoPo0BygZS5E+w9RtPxs3PnfYCeMFIJB+CcBS6T/OvEVNYg1rmRi1z4c2vwZtfDYDiMGFOd2DuHI6pUyiGGNsJF5/qyHRV58AjSwCQ7Ya6Vc+kRouaHrEiWl1xo2nJG9ejft2xw7Y3WoysvpLU6LlsNRB5fU+xqrHQLum6zn++nIf++fNYIqYDYJarmPr4OOyxjgBH17LE2i6CcBSSQcac5sCc1vQfvK/cjSe3Ek9uFe7dFdRsLGpYQEwJMaGEmjAmhWBOC8OU5jhjFrGTFAkUifCLOhMyMjHQ4QhCuyRJEtMnj+fTVV9SXOkvc2uhLLrhrwwcHUP8o38NbIABIpIP4YxnCDdjCI/B1te/wqXm8uHNc+I5WI1W5UWtdOPOLqd6xUEAlCgL9kFxhJ6b0uFn3ZTNCppbDXQYgtC+SRJT/vEKqtvDgqsewlS6n6iSrdwnyXg+2san187E3AEvwxyPSD4E4TCyxYC5czjmzuFNytVqL549FdRuLaFyzl6UcDPWPtFIRrnDjqSRLAZ0ty/QYQSM1+MGTcdoOfnOrjWVHnxelZAIC3IH/VwIp0Yxmzh31r/5dPVM7t7uH3obZXBx169P8kC/39I3JjXAEbYd0edDEJpJ13VKP9xO7daShjLJohAyMpGwiakdqjWk4Pl1mNLDiLisa6BDaVMFe7KZ++ZL5GftBCAquRPn3nwHnfr0P+Y+JQeczHlnGyX7nQBYQoyMvLIrPUeKmXaFpryaTsrCjQDM1Cc3lC9Y91ceu/9GDIb22b+pOefvM6udRxBagCRJRF7fk5i7+hM5tQcRk7thGxBL1fxcPPuqAh1ei5LMin+E0Bnml1f/h9fl4vw7pzHpnumU7N/H508+guo7divQ0i924XX5OP+2Plz8+/74vBrz399OWV2HZkGoZ5Ql8s8ZQP45A9hR6k/sD66OJnz1Fzx/wxUUzpmL1sFXcxaXXQThFEiyhDk1DFL92b1sL6F6xcGOd/lFoumw2DOEIy6O3etWs3PlUmTl0K/Q47VqRaeEkru9jHWz92KyKPjqkjZbmBjCLRzbPVfNxumsZuHcJ8iNLscdk8i3i7YxaZ6ZcqUK06XpdBnUA8XYsdoKxGUXQWgBRW9tRnerxNzVv0Nddil6fRNyqImoqRmBDqVNed0uNsz+gf3bt6BpGglduzNo0mVYQkKOuY+u6exaW0DutlJUr0Z0Sii9RidisRvbMHKhPdufmcmbH39MuGbnKo9/Vdw/xL5OlMnA83e9ikkJ7pF2bTbPx3PPPceMGTOYNm0azz//PKWlpTz22GP88ssv7Nu3j5iYGC6//HKefPJJHI6TG88skg+hPSqZuR21ykPsncfuE9AeFb25GdlmIOq6noEORRDOGFWuCr6aM51/lq7i+ZQaAAxeE2PP3x7gyI6vTfp8rF69mtdee41+/Q5NQZuXl0deXh7//Oc/2bJlC++++y4///wzt4rlhIUOzhBtxZNTSfWqfIKsMfH0nKGXXQQhkEItDs4d9zgx1hgs6y8GwJp5cYCjalmnlHw4nU6uv/563njjDSIiIhrK+/Tpw5dffskll1xCly5dOPfcc3n66af57rvv8B2no5YgtHchoxKx9oum7KtdVP6yt+MkIJIkVpQVhABICU1h/jXzSS26ii5z3mWr7wp+fuq9QIfVYk4p+bjnnnu46KKLmDBhwgnr1je/GAxH79vqdruprKxschOE9kYJMRF1XU8ck9Kp+jWX6pX5gQ6pRUiyJFo+BCGA4p8cybfhB9lb+QsrfHv48cNvAh1Si2h28vHJJ5+wbt06nn322RPWLS4u5sknn+T2228/Zp1nn30Wh8PRcEtJSWluSIIQNCy9IgHwFdcGOJKWoasaUsfqZC8I7YrBqHDd3RexU4/l1bGXc78jqkO0rDbrayU3N5dp06Yxc+ZMLCeY8a+yspKLLrqIXr168fjjjx+z3owZM6ioqGi45ebmNickQQga7pwKCl/eiGRWCB2bHOhwWoaqgyKyD0EIpJhQOzMfvwuAypBQbv/6HjJLMwMc1elp1jwfa9eupbCwkEGDBjWUqarKokWLePHFF3G73SiKQlVVFRdccAGhoaF8/fXXGI3HHmpmNpsxm4N7+JAgnIhnfxVFb2zGlBJKxORuKKEdY24HXdWRDCL5EIRAkySJmH03ct7KWCIrTUwpv5qfp/xCvD0+0KGdkmYlH+PHj2fz5s1Nym6++WYyMjJ46KGHUBSFyspKzj//fMxmM7NmzTphC4kgdATunEpQdQxpdjx48Ba60DQdXVP9TaSajtlmx2Aw4W8x1UGDuicEayuqt6AGY5wt0GEIggC8c/47LPzxcQB6bb6c8BuiAhvQaWhW8hEaGkqfPn2alNntdqKioujTpw+VlZWcd9551NTU8OGHHzbpQBoTE4OitM/56gXhROxnxeMuqmTme3/G847rqHWizIlMSLyxjSM7fboapJmRIJxhhsQPoccD/+ScT1dSbIpiwyfbGXZj33Y5sWGLTq++bt06Vq5cCUDXrk0XotqzZw9paWkt+XKCEDRkk4K3r4znExfDz70KR2QCkgSSLCPJMjs3LyM/N4uom3v7vyjqvyvqHvu/O4LzC8SYYA90CIIg1LGkp/CpuZAo22X8zRnJgbf/zIVTfoM1pH1d6j3t5GPBggUNj8eNG9cheuEKQnNVlRbz00v/ITwugbN+ey1Gc9PLjRVaMXm5mVh7RAYoQkEQOgJjnJ3Up0dz10cPIu+O5OOoPux+eCk2j849r54b6PBOmlhYThBO08F925k9/yHUHhY0FF7730Nc95uHiYyNa6hjMJnweTwBjFIQhI5CliW+S74I6gbVLelt5eWtgY2puUTyIQinadPm20nplNfwvLrawf5/raZUN6BJGhoaJo+XPrZRAYxSEISOQpYkHpz5NovGXsKOqFDGb81k4kXDAh1Ws4jkQxBOwy8fb+ax0P/g9LmQdH+HasloQBqroNd14ai/EJlQ24WzVQ1FzJshCMJp+u3oO7h2ayngBTrzwrpKpnX3YT/GbOLBpn1EKQhBam6ahRyXyt2qf8ibv9+odOhx3f12SWWuxYsqgRjzJQjC6Yq6oSefztzI7lo3xWaZn6MNvDXrYWZPmE7XsOCf+0MkH4LQTF5VY35xBW5JYocZcMG0sd1wGI/9z+nz/FLmbt8nlkkRBKFFSAaZa38zkP+tf5kPt37CC6YDYILl8+fS5bK1QT/8ViQfgnACqs/Hvq0HKN6vsX9HGY900ykN9bdfxJkMXJcQSajh+O0Z9V8DYjCYIAgt6b6BdxMRdw27t1xPZ0MWlXl92PLK8/S9+4FAh3ZcIvkQhMP4vF5yt24ib+cODu7awb6tBZjDrgUgvX8051eofBwKP2SkMzjBcVLHlOt+hWitFrUgCB2dpnnw+ZwYjeFIjVZ8vDExGr36j3z74iu4LVHcMLQ38vwVrBo3DKMcnC0gIvkQhDolB3LZNPdnti3+FVdVJdbQMBK69cAUOhkAe1gpF951LsWr9vFxdSn/OFiIrbgUiYZuHoC/lUOqa+uon0/sl2L/TL+6uPAiCEIz5efnsG79dIzGzciyhq5bSUm+me7dpzdcXpHSz+by4W/zYk0tBVGxXDznU/732lMAVKf3IqVHTy6//HIiIiIC+VYaiORDOOP5vF7mvfUKW379BWuYg95jx9Nn7HiiUlKRJImX7pwPgKr663eTjGTkelDCQ3Br/raM+pSi/rKKjj/R0OvKBoXZSDAbscpipIsgCCdP0zTmzvszcXFbQL8SryecktJfkaSXMRh0unR50F/RYIKpH3EvkLTkJ7L2bGs4hl2rRtu7nOKikSL5EIRgsfGXH9m6cC7jb72bPudMxHDYKsxRSTolByRc1ZH4vF4iNYmrlzm549rBGExi7IogCK3LVRuGLKvAKiQ5ksgI/7xCDsfgo9a/YvQkclP78Pmb/+Ze7T1MymIACquuAHq0UdTHJ36GCWe8mspyZEWh+7CRRyQeAOdc36vhsa6B6vW3dihG8c9HEITWJcsyF1/8N8pKb6S0xEJVVSlIg+jT+wuio8855n4pKSlM71uBSfE32Xq1KMKs3dsq7BMSLR/CGa0wZzdleQdQvV7KDuZhc4QfUWfD3C3Uz87x5v2fMuqasShGOeiHsgmC0DHEx8dz1VWPN3/Hq96mrOeNVN59KzUFZnwXqvRt8ehOjUg+hDPWrGeexpftpMpbSmhUDCUHcik5kAvo/v90HV3XiUvV2bF8KwbzEDQ9kfWzN2EwhgY6fEEQhKPy+arI3v1v0HXGFl7OrwVmALTkkABHdohIPoQzku7TSC/qTkSMfybAT/f8nTmvv3CogiT5R6xIIEkSmmZCVjohKQ6qSjU69RbJhyAIwanWdYD9+99H16F3fh+eu2caDmMZj9iqAx1aA5F8CGek6jX5RJjjMfeMwLu3igc+/rYu2ZDE5RRBENq10JAMKqz/ZPq3JgBKpSjMkgOPO3h+NIkec8IZSgIZTImhIEvIsoIki34cgiB0DN07ndvwuEy3ka+FUaFZAhhRUyL5EM5IhigLaKCWuZCCdAZAQRCEU9UnycGeZy9EUupmVw4zgiF4vuvEZRfhjONzVVG8ZjUeWwVaWRW6VUXTPMiyKdChCYIgtBhJktBV/8yHcqU3qNZ3EMmH0GF5XD6K9zsp2ldFcW4VhQd2YIiYTWSPuRCH/1anatvF9Onz34DFKgiC0Brui5nL/4omABBm8AQ4mkNE8iF0KLquU7x+F5+9vv8oW8Nh3xSqD/Zm+NBwItKTQNPYWf5XvN7yNo5UEASh9dUnHgDeKjfEBDCYRkSfD6HD2Pav/2PjWWeRddf0I7YZPVUNj6sL+7A7+3sK9K8oMfyCbLA0XRlOEAShA+j/Tn9Gugwk+GB0DYRa7YEOqYFo+RCChkf1ICMjl+xDrtoLe5eBtwY0H4QlQWQ6haZoyuxdsOsaJc41bKrNZ9uKEiZtjqKzfThfd11FWHkJ5657BFvvDNQaF5LRiIyOp6SWioIq3GHh2C+2o6rVeDxFGAx2IiNGBPrtC4IgtJjtGT35BKi2PkN5RHc0yYBdHgiIheUEAYCfC8p5ZNNePHk38NmzPgC6XpaP0dq0d9S8yGFcn/EcIfOXk2W5iUnpnfwbzHCP/WUAUuw92G/cQY9vZiKbzW36PgRBEIJNaYTO5piDpBZXYCJ4FsIUyYcQMDVVlexYs5qPZ/7CcLUaydqZopBcYpy1+GoUf/LR/QLYvwaiuzFWMiBVefFYTKxw9OP+imq+DtMIZSC7qaAzDnS7RK9RE0XiIQjCGcvrVilKHsbmrjfhrVkE7jXsjXbgkmSOXDozMETyIbQpVVXJyspi/fr17P/hcySPm371G2tg16UXkVZVg/nOyRDXDUIO9Y5y+1RGbd7Dkkgzl+OfCr1fiIWX+3chTFZQDDLJjGn7NyUIghAkcjYX88NLm3D3uJpyaw6SPRVdDcfi9mCLiAp0eA1E8iE0oesa1TXZeNxF+HyVIEnIkglZNiMrZv89FixaMrLZgGQ41GdZ92loNT60Gq//vtqL6vSgVnjILtzLdj2Xg6UFVFdXk5CQQO/Lr6UscytVLjdlZaXomoY5PomqyWOQu/Q+IrbvispZUu7k/3okM8wRwoaqGu7bvo875s3iM898KM0BWyT0mQy9LhOdSAVBOOP88NImCu17+arfv5uUy7rM/dyLDVuAImtKJB8dmKb5+0zI8vEHNblceZSWLqW0dAmlZcvwektPeOzwvROIy7zhhPUkk4wSZuY758KGspiYGGJjY3FLEvbeAwmRJGJ8PjZt2kRWXj5Zn39OdHQ02dnZFBYWYjab6d69O0MTkghVZP6auZ/wgy7KDzjp5s3jQ+90PGFJmDoNhfJc+Pw3kHExXDvzhPEJgiB0JFPvSmHmkq9Jz9cxeSHEpTOwOpai2kLUqWqgw2sgko92TlVVDh48SEFBAU6nE6fTSUVFBaWlpZSWlqIoComJicTHxxMVFYXNZkOWZfLz88nPz+fgwS2kpS0kPKKQsNA+JCVOISJiBBZLMkZjmP81NDea6kbT/LcNy29DtVQQOTUD3adBXQODpMjINgOyzYhsN/ofm/wdnCxP/IJL95CWloamaZSWljYsWV9/i4+PR1VVTCYTn3zyCZWVlcTHx1NbW8vKlSvp3Lkzi6Zcy/Rvt7BicwldU8O5wCxh2uvl45J0zh48hqTYYshdAbt+CdT/EkEQhIApmHIpE4AJTUrzAbB4dAiS7nAi+WjHdu/ezeeff05tbS0Adrsdu91OWFgYXbp0YejQofh8Pg4cOMCuXbtYvXp1Q2uI3W4nPj4Op9OA253O2WN+wGgMP+rrHN5ByVgVDZpM2Rc76xKP+uyDpvd1S9ID3FA7htDxnXBMTD3h+yovL+f5559nwIABDBw4kNraWj755BN2795NgtlEqmJgu9XI5d1jibQl83Leb7ha/4aY+b+C0QYDrodJ/zjJv6IgCEIHYjCAz0fal1+gmY04jSqWTVnk/fFPKErwnPKDJxKh2ebNm0dkZCTnn38+iYmJGAzH/9+p6zputxufz4fdbkfXVZ555q/ISsgxE4+jUaJMGGpshJ2fBnrD0Rs9pu6xjl5XJikytgEnN7VeeHg448ePZ+HChWzYsAHwX6q55ppr0DQftw93UlpZy8u/7qTWB11jJpN2yZ+5MMMBBiuc4DKTIAhCe6dpOkVON+E2Y8P3rKbrmAcMRI4Ixx0Tj66DSdOpyl/ur3CCc0RbCp5IhJOmaRpLliwhLy+PCy+8kE6dOp3UfpIkYbFYGj03IElgs3Zr1uvLYQqWuAhCeyU1a7/mGDNmDMOHD6esrAyTyYTD4cDnq2T1mstwOncwJRWu6QQ6EsOGfkVYWGKrxSIIghBsOj/841HLH891MmzNamrnzDlim07wdMIXyUc7tGzZMubPn8/ZZ5/NoEGDTutYkqSjab5m7aPrGpLU+h8do9FIbGxsw/OS0kU4nTvI6PE0CQlXUlq2jI0bb2X1misYf252q8cjCIIQLJ64tDePzdrKWemRTBmSgiJLSBIYxz/CweydSJL/B6ckSSzNLmFBmcTPouVDOFVer5dFixZx1llnce6555728SQZVK156yzruurfsY1FRozCak1jR+YjZO58Al33r9A4aKAY1SIIQge25UvY8hV0Px9UD1Qc4PqSHNJMu1mzryu1ajrd40JA19B1HaJ0/NdidNA1unWqJksxI8vB0/Ih6bqun7ha26msrMThcFBRUUFYWFigwwk6cz7/nKVbtwJg9vhPvlKj/4UNHy1dByQkjtwmQUP/DKfVQkrKZnr1diJJct2lGBlJUpCQQVL8jxtuMuXla4mPv4yMHn9rzbd6VKrPRWXmu+gH1mAwhWPrdROG2H4n3lEQBKG9eioefP6BBcgG//e7fuxhs5ru/+bXkNEBk1RX9/GKVg2zOedv0fLRzqQ6naxxuRgYU9d5s6Fjp173sNF9/bYm5Q0loOtU5W8krbOZqKiB6LqKrmvouq8ug1bRqS9T68p8REQMJybmvLZ943WUH/9ExLr36v4BarDgDRhyK1z87xPvLAiC0B6NmQ5LnocZ+5t2qNc0NE1FR/L/aJT9l1nqazSs5LLydfjlL20b8wmI5KOd0L1eSt58E+31N5javTtpzz3XIsfdOWIkkb1/Q3S3O1rkeK1K9cK699EzLqL64pew+aqQn+8La94SyYcgCB2XwYLuqcX92ARkuwH/r8i6yypoDT9C6y+z+PmfS7qGrJUi6wRRd1ORfLQLuqaR9/AjVP70E5HXX0/UnS2XKGhuN5IlSGadOQFVNrC6128Zvu0dQnb80FDuGztDfJAFQei4uo6n9uefkNDRFTP+OZSkpvdIdX3xpEPzL0kyOhI+VxqemkQcAXwLhxPf2UFOragg/8mnqPzhB5L+/S/CJk1qsWPruo7uciE3Gn4bzH4squC2mN/y10uu4qyaXeR5df7qSSUxNIWfAx2cIAhCa4nrTYXtCWyDY3Gcl3bUKv6ZojV0TUfXNDRVRVc1dFWndnUBNQsOiuRDODmVO3bwxmMPYvSpxCdFk/nlR/DVx0h12a4kNZ5Z1D/MSmrIhGm0XaqrIjXUqy+rjQ1Hqiwnoq3f3ClIMhuRgM/VaLZEJpNV46bQWcuUiJBAhyYIgtCqamurqFxTSmHFXnRdR6104ymrAVVDqoGQ2jBkSfb3/UBGPmxEoq9udGCwEMlHELOk+qci9xoUcqPCoKqMcORDnUwb1dUbrvnVPW+87VCFI7ZVx0WgH9hDRksH3woGOex8PbArH+aVcMDtoavNzF+6JDI2MjTQoQmCILSq0ooDxHvSYW19iQ2PJuOTfCDp+AxetC5GFJMMsg6y5r8Ko8gU7dtD5ual/JbxAXwHTYnkI4iZrFbun/kN25csYNU3n1F2MI/wAQM5+/qbiemU1iKv8enjf8YSFd0ix2oLNfnV6OtLMFa5sUZYCQkJg8hARxW8dF1ned5yNhZvRJEUhsQNYWDswEOtYkfbx+fDuWgx7p2ZyDYb9tFjMHdOP/4Leaph+3dQkg22SOgxCSLSWvbNCMIZbFPNd+zWrfQeOgBJ8i9nIZv8l1nqO5/quo5Wt1AnvrrLMLpOmbOAMvfBQL+FJsQ8H+2EpqnsXL6E5V98THlBPiOvvo6hl05GVpQT73wcHzw0jYRu3Znwu3taKNLWM2dbAbe9v4b+yQ7So+1szatkV6GTZ67oy3XDTm6K+TPNI0seYVb2LCItkai6SoW7gt5Rvfnk4k+OWl9XVfb95rfUrFmDEh6OVluL7nYT+dvfEvfnh47+Iq4KeG0slOVAaALUloLPBRc8B8Pvar03JwhnkG9uHUG2M+qU948wu7jl/bktGNGRxDwfHZAsK2SMGkvXs0ay/IuPWPrph2StXs4Fd08nKjnllI/rcdVgtFhbMNLWk1deiyJLjOsRS+cYO+E2E7sKnWzMLRfJxzHM2TuHkYkjeWTYI/g0H5d9exlbS7Yes76voICaNWsInzKF6HvuRi0uZs+Vkyl9991jJx/5m6FsD5zziH9F4ZJd8P5l8POfRfIhCC3k0sEKbosZ6dL/1fX5k0GW6iZ/rBvpIkv+ySFlBUmWD9VZ/hIs/k+g30ITIvloZwxGI2Om/oauQ4bz08v/4YOHfk9SRm9AR/X5kGQZe3gczoow4jtHY7JYMJjMKIqMpMjIioysKMiyhKzIlOcfxNROko9rz0ohq9DJW0v24HT7iLSbmDa+G9PGN29hvDPJtEHT+Oeaf3LR1xc1lD064tFj1jckJBA+ZQrln35K+aefNpQnv/zSsV8kZRhkXAy/Pu2/AZhC4RYxBkkQWsrf7BprPVtRZk2iUNKw6TqhyNhQ6KRY6RqWxg5XISZdYpa3oGG/ZK+P/UYDfzP5uCKA8R9OXHZpx7weN2u/+5qivXuQFAXFYED1+di7KROXs+DEB6gzYNLtjP/tpa0YacvSNB2XT8VqVI7bd0HwK3eVs710O7Ik0zuqNyGmE48O8uzfj3vnTmSbDWu/fsg224lfqCT7UJ+PhAGgiN82gtBS+r7XF4BLzQl0Dkmm1ufG6atmRfU+svECoOg6/dxu1h9j+oTNv9ncqjGKyy5nCKPJzPDJ1x5Rrno1Vv+0hzU/ZKMoKufc2JXQSDOqT0VXdVRNQ1c1VFVjztvbiO40oO2DPw2yLGEziY/uyQq3hDMicUSz9lHDY6lMtmM0K1jMJzkPTFQX/00QhBY3Ke0CiirzeWziq6BLdeMddTRdQ9e0hjk+/B1P68v8j2dlzeLF7a8H+i00Ib7BOyDFKDP80i70HJHIj69sYtGneYya3JVeo1OatBTous6ct/MwGE+v06rQsSz/Jpv1v+yr+yIDo0Xh4nv6k9gtPLCBCcIZLKVA4+ZH15DNkGbvOxT4Z7gEN7d8XKdKJB8dmCPGypV/HMzSz3exYGYme7eUcP5tfVAM/slnNJ//5GIwysc7jHAGqa5ws+7nvWSMTGDQeZ1w1/j48h9r+fpf67jn1XMDHZ4gnLGuOutWyvkR59AMnKP71k0UWTeVen0HVCQkuW6qdbl+mnWZ0O+XELMpK6DxH04kHx2c2Wrg3Jt6EhplYdV3e/DU+rCGmgDwef3LLCui5UOoYw01EZcexo5lB8nbWYan1v8Z6TYkNsCRCcKZLS6hC+VA96t+i+OyywBY+q/vKdlXhe7z1V1iqZ/yo/Eq5pCnTcDeuS89Axb9kUTycYaQCrcBVt7/01ykJnOcWjF8ewvM3ULDIkUNixMd9hjJv2KiORSu+wQiOwfirQitSJYlrpg+iKx1hZQccGIwKaT2jiIuXXT+FoRAkkwm5o97CX6C6Fnvo0syJYZEwEaUdrDhkrokHbrVN4x4Y1LJ1fsEMvwjnFby8dxzzzFjxgymTZvG888/D8Drr7/ORx99xLp166iqqqKsrIzw8PAWCFU4Hb3Gdcay/THUsHRI6N+QIStyGUldJoJhvL9A12hIl+uXZ65fulnXoXQ3bPkCynMDknzouk6JqwRN14ixxhx1tIuu67h37sRXWIQxKRFTeroYFdMMilGmx7D4QIchCEIjjb/DTDYjEhop5DHk2oEkjjr+JdEtiw6w6OPM1g6xWU45+Vi9ejWvvfYa/fr1a1JeU1PDBRdcwAUXXMCMGTNOO0ChZdjSe9LHNht6Xg2Trzv1AxXt9CcfirHlgjtJawvW8tiyx9hbuReABHsCfxn+F85OPruhjq+4mH2334572/aGMlPXLqR99BGKGLotCEI7ZrQoDL0onYETm9f/SpYlgmtSjVNMPpxOJ9dffz1vvPEGTz31VJNt999/PwALFiw43diEluSu8t/vnH16x9H848lRTKd3nFPwxPInsBlsPD/ueWRJ5r5f7+Oeefew4cYNKLK/30rFt7Nw78gk6fnnsfbri3PRYvIff5zcO+8i7aOZbR6zIAjC6dC9XpwLF6JERaFIOqW78tinlKKrOpqmgaqh1U2foKs6uqahqXVDbVX/8Nu8fB2Q0TW9rkNq4J1S8nHPPfdw0UUXMWHChCOSj+Zyu9243e6G55WVlad1POEYsub576/79Pj1TkStW5Y5AC0fGREZ/LL3F97b9t4Ry0XXs48aifzSS+T98Y8YYmLwFhYCEP3AA8zamMfSXcV4VY2+yQ6uGZKC3Sy6PQmCELx8ZWXsv/f3AChD/8KO2gR2bKppxhH8nT+Mnip0VUWSg+M7r9lRfPLJJ6xbt47Vq1e3SADPPvssTzzxRIscSziG/C3w7T2QNgZSR57esdS6lg+57ZOPp0c/zZD4IawtWIuu6zw09CEmd5/c0OoBYMnIoPNPP1H1yy/4ioowJiYSev55PL0kj3eWrufc2Bp6SbtZttHF/77rzrK/XYPVJEb7CIIQnBSHA4DwKVO4dFIvampBqlseQ6pbKoO6pTMkg4IkK8iKhGRQ/AuPGhSc8+ZS+vdnkbgwwO/mkGYlH7m5uUybNo05c+ZgOcb0rc01Y8YMpk+f3vC8srKSlJRTXyhNOIrcFeBxwnlPnv6x1MBddjEqRq7pcQ3X9Ljm+PXiYom88YYmZZv2b+e5sC+4tvIrfMCcCBtdzSae//47Rg69g7OTzxadUgVBCDqSyQSShKVXLyKGDyTyFI6hhtuQdV+Lx3Y6mpV8rF27lsLCQgYNGtRQpqoqixYt4sUXX8TtdqM0c4l3s9mM2Wxu1j5CM/W6HH74A2TNhcSBp3eshssuwdF0d7IendSF/u9+xU/qUB6Kc6CH7iTN48Vbup6P5t9LnC2OuVe37nLTp6u6vIz1P39HwZ5sDEYTaf0H0uec81AMx/5/4d6zh/JPP8Ozbx9KRDhhky4kZPSo475OXnktH6/ax+6iasKsBs7vHc+4Hkef56PcVc6+qn2EmcJIDUsVCZwgtDBJkkDXyX/sMWrXrcUxeTL2s846tYMFUa/TZp1Bxo8fz+bNTRemufnmm8nIyOChhx5qduIhtAFdh4X/AKMdel52+scLYMvH6eifFofe7xombfqMR+0pDKp1c19pOd4e53OjcyMFNSe/EF8gaKrKJ4/+iVpnJck9++CprWbumy8z7+1Xmf7xrKPu483LY8/kq1Dsdiy9euHatJmKL7/CccUVJD77zFH3Kav2cPELS1A1nb5JDnYWVPHxqlzO7x3HazcemtZZ13WeXvk0n+/8HE3XAEgNS+WV8a+QEiZaLgWhJYVfOwX39h1UfDuLim9nodhkqJ+vqUk+cbTkQsff6CGBprV2qCetWclHaGgoffo0najEbrcTFRXVUJ6fn09+fj5ZWf6pXDdv3kxoaCidOnUiMvJUGoyEZqsqgPzNkLMIts2Csj0w4QmI6X76xw7gaJfTJV3xOgy+hYe3f8RzRUu51moB50ZCjCE8N+a5QId3XKrXS1VJESl9+pMxaixel4t9WzahH+fLxJuXh15TQ+hVk7GPHIk3L4+Cvz1JxddfHzP5yK90UVrt4fphnbigTzwFlW4e/Hwjs7c2Tc62lWzj08xPubn3zVzU+SLyq/O5d/69XPj1ha2+cqYgnGkSHn8cgJq7Y6gpMkHSIA5NBCkB8mEzix1W5izEWL0FKYjaB1q87fzVV19t0oH07LP9czC88847/Pa3v23plxMa27cS5j8JOYv9z21RkHERXPhP6Dq+ZV6jocNpEH2KT5YkQeoIrkgdwQW+WnaX70aRFbo4umAMwOid5jBaLFx43x9Z+MHb/PDff4AkkZTRm/PuuO+Y+1gHDybqrjspe+99yt7/AGSZkAnjSXz66WPukxxh5YqBSXy+dj8zV+4DYETnKJ6/dkCTep3COpFgT+DD7R+yJG8JJbUlANzQ84bDDykIQguxDR+JzRoBV7/bvB03fgpf387RW0YCQ9L1ILoIhL/DqcPhoKKigjAxKdSJ6TrsXw0bP4F170Ncbxh+N3QaBo5OILfwonGbv4Avb4UZB8Ac0rLHFk5I13XcNdUoBgPGk1jq3uPyUZBdiq+4lKjucYQlRByz7qo9pdz2/hoqar0NZb0Sw/j67pGYDUcmmxXuCuYseZ/adeuxKRZ6jr2cXoPPO7U3JgjCiX14FRjMcG0z5yza9Bl8dRs8kg9Ga+vERvPO3+2r16DQlLMIvrjZ39IRlgxnPwijp4OhFS+JaHU9poO8paBD0nWk3FVYCraA0Qadx0JY4jGr79tawuw3t+Kpre/lnkePYfGM/03Po0409N7yHAyyxA/3jSY5wsZt769h1Z5Sftx8kCsGJh9R3/fB5/T+58uHCl7/ldwJ40l+4QXR8VQQWsG6A4OpKIdEz7todatfNL2XGp7XL6Gh66A7iwipmUjvIGprEMlHe6R6YefP8OOf/MnAdZ9B14kt38pxrNcGCJKJas4Yug6f3gA7vgdJAd2/2izjH4Mx04+6y7rZe7HYDVz54CDMNgOfPbOazJX5DJiYQnRyaJO6BXsqGZzloXuezC9/W0OeSWen2QMKnJsRd8Sxi2qKWDrnXcJH92Dk399EUQzsHD4C59x5Lf7WBUHwW75nGADblh0qk1CR0JAlHQkVWdKQ0JHq79Hx6ZG4tUH00AxBc9IPljiEk1G4AzZ86L/EUl3knzTsyteP++u3xWk+QGqffT7as6p8f+Ix8EaY9A+ozIMXB8O8J46ZfHQdEsfCjzKZ+e9fqLEewGuuRTYa2ZMXRlTS4IbWCV3X+eHljdjDzXS5KI3sAiemNSXc5rFwx0vjMCiHklpN13h06aN8m/0t/vmKKoj67AKeXD6a+E4jsfY69mUdQRBOT3r/aGqrPFw+fRCSLNX1Jz1xK2PmynzmvrMtqL63RfLRXsx9HJb8B6yR0G8KDLwe4vu2fRyaT7R6BEJoPPS5CtZ/4L/Vu/Cfx9ylz9lJKGEuPv1mEREhMXSO74ZPruWHH79nR+Z2brzxxoa6ZpuR6goParmHToqR+vUvGyceAJuLN/Nt9rfc1vc2Jqqj2Tl7NX9JeZG7x8/jp+3+SzBqhRtDeMtMQigIwiEmiwFXtRfF0MxW7vrLLUF0NVScRdqDqgJ/4jHwRrjoX/4OR4Gi+UR/j0CQJJj8Joy6Dwq2+juNpY0Be/Rxd7NF+P+JJ6bGkpKSQGlpKQAVFRWNDi1x2f0DWPvzXgpzKpFkiUHnpzLogtQjjtfZ0ZmkkCTe3vI2P/M9pUn+401NHoOiKKhbVGq3lBA6Oqml3rkgCHVkRUJTm99vo36PYOqLJZKP9sAWBbG9oXCb//n276E0298K0u08CD3ymnyrUb2i5SNQJAkS+vtvJyk1NZWLL76YlStXkpmZid1uZ8yYMYwbN65JvZAIC2On9mhS5q6pYcWXX7A/cxv5bi8HE9IoHjqW8wa+TLRrBZuyXkPRquhrhgRpNtsSZ5Ni/z1JI0e3xLsVBOEwsiJRXe7GWeZfjLVxLqFpOrqmo2k6mldFK3X7n6satTmVWGVEy4fQTKoHjBZQffD6OH8SYg7zr9eia3D5KzDguraJRVx2CRxdh/xNULwLLOGQOgJM9hPuNmTIEIYMGXLCeoeb9a+nyNuViTO9B/trvXT99Tsif/2Of9z5FNCLd0IK6ZpyMymW23E6d7Hx4HXkOl6gu3x/s19LEIQTM1kMOMvcvDdj6THrpJlkellljI0ykxhgYqgBVB2CpNuHOIsEu/J9/rHd5fv8Ixtm/xnO/Qucdbu/+f2dSfDNXSL56OhUH3wyFXb90rT8hi+h64RWecmKwgIiE5PZlN4Ll6bB3h1NtoeEj2Vf7hvs442Gsj69/9sqsQiCAIMvTCOph79T9+FTdMmy5O+E+t5Wf4HdiDIxFUmR0LPLUTcUcZQR9gEjziLBbvbD4K6COxZCRBrs+hnmP+W/1bv5p7aLR/T5aBWax4Mky0jHWiQuf6M/8RjzIIya5m/9ePNc+HAyPF5x9H1O04W/f5B5b71Kr58+8YcQk8jc0ZcQbzLyZLckRse8QmXlRqprsjAYQokIH4HRKCYGFITWYrYaSO0Tddw6+yWw9okm8toMJMWfbVQbZMo2FLVFiCdNJB/BrPIgbP8OJv0fxNRdj7/xG3/Te0mWv89HpxH+SzJtRfUG1XCt9q562TIK/v4P3JmZoCjYhgwh/rHHMHdOb1oxtrd/ReLF/4SVr4K3xl9+8X9aLbbE7j258e//xet2gSRRjsx0XSfOZESua9J1OAbgcAxotRgEQWgeU2oYkkFuSDyARqvZBk/Th0g+gpk9BkIT4eDGQ2Wn0OmwRWk+kEXLR0vQfT723zcNc48eJDz9FJrbTcHfnmT3hRfSc8f2ppWNFrh1DmTPh+Kd/j4f3Sb6h+C2svpp3GNa/ZUEQThdss2IVuNtWlife7TBPJQnSyQfwawkC5z5YD9+M1ubEn0+jpBblcvLG15mc/FmZElmSNwQ7h5wN9HW4w+DRVEwxMbiycrCuWQJuttzgvpG6H6+/yYIwhnlyeVP8tnOzxiRMAJN11B19Yh7XdeZXDKOEQW92fXIXDQ0NEkn1GcD/DlIsLR9iLNIMCrPhay5sPotCEuCcTMCHdEhos/HEe6aexce1cOE1AmomspHOz7i852fn3BpeUmSSH3vXUrefRfX5i1IRiMxf5hOZKPJvwRBEAAqPP6+XXajHaNsRJZlFElBlg7dy5JMgd3Fuvy9KLqMjIysy+wsXcEePZf/yMEzDF4kH8HA54a9y/wJR9ZcKNrhX78j5Sz/pGKtuAphs4k+H0fwql7MipkQYwi++oX3TpIhJoa4P/6xlSITBKGjmJQ2idk5s3l0xKNEWJq3jEHljk95d9U3YpKxjqqmpoby8nIqKioabpWVlVRXVzcMi5IkqeEGIBXtQHLmI+n+k5ZEdyR6IFkjkMpM8MUXSHzpn8Mfibr/6hYMAknyL1vY8BwdDf8Kh6ruX+Gw8WNVB02XUOvKkiy1XBJ7ECTZn1RIsr9fiaQcVlZ3n7vC399AaPDyhJd5ft3zfJb5GYqkMCl9Eg8MeiDQYQmC0IGEmvyLQVZ5qpqdfPh0H4Ygu1weXNG0IyUlJZSVlZGXl8eBAwfIy8ujqqqqYbuiKDgcDsLCwggJCUGW5YYERNf1hhtmEzqR/mWP/RvRAU3X0VX/NTzqtjXUgbq1CuvvD6UjOhISOooEsqQjS/gfo2OUQZZAljQUWWJ9eSgVqplLjGWgaXXrMnvq7tW6dZkb3TTVn3hkXNiWf+qg1yW8Cy+c+0KgwxAEoQMLM/uHsVd5qk5Q80g+TSQf7V52djYffHBoYS+z2cyAkG4M8QzBrCvIdgOWvtFETuyM3NzFf9qYbc4ctm3bBlOeDHQogiAIwnHUt3zU9/1oDq/mFclHe6WqKvPnz2fp0qWEhoYSHx/PhAkTcHisFL+0EUuPCEydwvCVuahZeJDC7RXETx8c6LCPy+v1YjSKzqOCIAjBLsx07JYPTdPwaV58qhefz4eq+vBpXlRVxad6qSgtxqwF1+k+uKIJQgUFBcyZM4fc3FzcbjcDBgzgkksuQVH8nS49eU4AdJ+Grmrg0wCQjMHd6gHg8/kwHGtGTUEQBCFo2Aw2fvtjKlt+fIH1hv8i6RKSDpIG8kkMoB1vsqNP1YOm06k48xzHihUr+PnnnwGw2WxERESwYcMGnE4nN9xwAwCmxBCibuyFc+kBatYWIocYcVyYTkg7WFJctHwIgiC0D0rdKEPJYiR8TC9kRfHf5PqbjKIYkGQZRVGQJP9zRVGozMyheOXmoEk8QCQfx7Vq1SoA4uLiGDx4MBaLha+++oqsrKwm9ay9o7D2DqKJwE6SaPkQBEFoPyISkug8+CzG3Xhrs/Zbo37N8g07WymqUyPOPMdx3nnn8cMPP1BQUMCPP/4IQHJyMldddVWAI2sZouVDEASh/bCEhuKqOoXRLh4PBpO5FSI6dSL5OI6MjAwyMjLwer2sWLGCxYsX4/F4sNvtgQ6tRfh8PiyWNlyUThAEQThl1pBQap2Vzd7P53FjMJlaIaJTJ5KPk2A0GhkzZgxpaWm89dZb7Nmzh+7duwc6rNMmLrsIgiAEv4e/3sxHK/cxxNadytJS3nrkff98UHXzPWlI6Lrkn2ASCb1ucsn6CSfdqkKMbRS3BfZtNCHOPM2QmZkJQGRkZIAjaRki+RAEQQh+u4v8oyrX1ISBJQzUptstkkovsxMJ/0SSiuyfTVuRJGQJVlTZKdHD2zzu4xFnnpO0fPlylixZwsSJE4mOPsFqpe2ESD4EQRCC37s3n0Xvx2ZjMypEhpjQdN0/KbWuU+nyERtq56sHLz3m/m8u3s1/5ogOp+1O/QRjgwcPZtSoUYEOp8WoqtowX4kgCIIQnCxGhexnjr6sxeuLsnlhXtZRt9Vz+zTMxuD6rhfJx0mQJAm73U7xwVzUrbNQqgv8S913OSe4VpxtJtHyIQiC0L7FhJqpcvuo9ahYTUdPMDw+DXOQLfchzjwnQUUlbrCB3HX/5o05bka6vPRz1fo33rkE4vsGNsBTJJIPQRCE9i0mxD9isdjpJiXSdtQ6bp+GSSQfwc3tU1mWXcK+okosWi0ZETJP73yC7c7tJIQYqTZF8JLmYpyjOy9smAtf3AL3rg502KdEJB+CIAjBb8uWLXzxxReMHDkSRVGarIy+3+lf6/zuN3/FZqTJROtS3TroOVVgNIqhtkFrb2E5U15bQX51o67EsovQHtvp4U7hqYpsVG8O1ybFs6CirvPOlJmBCbYFqKoqkg9BEIQgt379egCWLVsGQHh4OJIkIUkSKjJdLbGUOhVK6+rr9dOo64AEXo+XdGPz5wdpTeLMg78FYNWqVTw/fwf51XF4+kWgxVuxFbrQNpRiqryALMccrjabgHhMksJ/e90G198GhuDKJk+WpmlomiY6nAqCIATIuvU3Ula2jKjIs9HrWil0XSU97V6MxnBCQnoAcOONN7J48WLWr19PaWkpqampTJw4kZCQEAAeOMHrfPvttxQVFbXmW2m2Mz75qKys5MMPP6SoqAjfoHNgXQ2mTWVIm8vQ/J8FrhlzL7dnPExWeRYmxUTPyJ6YlPaZdNTz+XwAouVDEAQhQNzuAgBkxQJIVFZuxO3Op6zM38IxbNjPhNi7ATBmzBhGjhzJ+vXrmDdvLpmZ2zjnnHPo06cXmq6B7l9RXdc1dF3D3+zhvzTj8ZSgKMGzqByc4cmHpml8//331NTUcMcddzBXM7LMuo9O1Ro2r06W5sUXaeGiLjFEWGwMjR8a6JBbjEg+BEEQAis56Tqysv+Pfn1faShzuwtxuQ6wZu1VrFp1EeCfz8M/X6nfkLpTkbP6bVasPPHrREaB1TYAaN6CdK3pjD3zqKrKN998w65du5gyZQrx8fHcAMSbjfxYVE6FT+UCm4UbE6NIsrTvVo6jUVV/vxaRfAiCIASGotjRNBe6riJJ/kvgZnMsZnMsffq8gNdTBpKEhARISJIMSA1lFRVVOKur/dslua6zqdyorv95adk/iI8PDcRbPKYz8syjaRpff/0127Zt46qrriIjI6Nh24SoMCZEhQUwurZR3/Ih+nwIgiAEhqL454lS1VoMhpAm2+Jijz6pWGMJCSf3Ous3LERRgmtB1DMy+Vi/fj1btmzhmmuuoVevXoEOJyDEZRdBEITAqk8Isnf/G0Wpn6NDP1RB1w/bQ8dz0Ikn14kxwdaout5wrzd57n9YpewgPGxI67yJU3RGnnlyc3MB6NSpU4AjCRyRfAiCIASW3d4Vu70bxcXzG8qkxjN1NOkj6n+iVrnRQ3Vw4r/8Ih1RselzCSSXAUtNcK3EfsadeebNm8eGDRtITU3Fam2/U6OfLtHnQxAEIbCs1hSGD/u5Wft4Djgp/Wg7vhIXCQ+fhRJmPuE+Bc+vxZTuONUwW8UZdebRNI3ly5cTExPDTTfddEb3dxAtH4IgCO2PKSmEiCk9KHp5IweeWUWtdGS7BwD6oXIzUOMwE9F2YZ7QGXXmcbvd+Hw+hgwZckYnHiA6nAqCILRXpgQ7hiFxZC7Nwxpiwh5R1/pRn21I/os3el1ikrunklCLgfQAxXs0Z1TyUVJSAoDH4wlwJIFXn3wYjcYARyIIgiA0h2RU+HLufgDGT0knY/iRw140TWPb4vVsmDOP4rIC+rguATKOqBcoZ1Ty8euvvxIREcGAAQMCHUrAeb1eQFx2EQRBaK903cfsV95h7ptOjCYPuq7T7awRlBcUk7t1GaqnFEkJQVedqL7gWn39jDrzhIWFkZ+fj8129GWHzyT1yYdo+RAEQWh/7nxxHM9ffykAPhe468o3/JwJQFhkd/pMuJ4B54/irbt/S2SC6HAaMIqiiEsudbxeL4qiIMvyiSsLgiAIQUVWJAwmMz6Pm6zUDAqj4rG6aqi12lk+aCzz7r0Rfv2JnEdgPOAbkBXokJs4o5IPk8mE3W4XnSzx9/kQl1wEQRDaJ0mSmPbBl1R7PXRdtAZZLQPdh6SryN7dZKYk0iM371D9g8UBjPZIZ9TZJz4+nmXLlnHw4EESTnZe2g7K6/WK5EMQBKEd6/uevx9H9FG2/fUGAAOfPesfXFAQHk6fNovsxM6oNvfevXsTGRnJggULAh1KwKmqKpIPQRCEduymXjc1eX7vgHv5/JLP+erSr/j7uJcw2ftww4MKd9yrsOaiLgGK8ujOqORDURTGjh1LZmYm+/btC3Q4AaVpmujvIQiC0I79cegf2fybzdw74F4AXtzwIkU1RXSL6MaFqWez9qqP+fm6BZSFSvQMtQQ42qZO6+zz3HPPIUkS999/f0OZy+XinnvuISoqipCQECZPnkxBQcHpxtli+vbtS1JSEt98803DFONnIlVVRd8XQRCEDuC60u48VTwWgLvn3c1lb4zh9y9fyP0vXcQzb//GX6mqOoARHumUk4/Vq1fz2muv0a9fvyblDzzwAN999x2ff/45CxcuJC8vjyuvvPK0A20psizTs2dPysvLGybaOhOJ5EMQBKFjKHnzLTI+XsnH36TSq9hCWJmb0ppi8l1F5HoK6ZGrk5brPvGB2tApXfR3Op1cf/31vPHGGzz11FMN5RUVFbz11lt89NFHnHvuuQC888479OzZkxUrVjB8+PCWifo05efnYzAYKC4uJikpKdDhBIS47CIIgtAxyFYr9pEjSf7ff/n0sG2+sjJ2jRhJ8vDkgMR2LKd09rnnnnu46KKLmDBhQpPytWvX4vV6m5RnZGTQqVMnli9ffnqRtqALL7yQ2NhY3n33XbKygmvsc1sRLR+CIAjtW+l775E18Txq1q5Fq609ah29bm4ryWRqy9BOqNktH5988gnr1q1j9erVR2zLz8/HZDIRHh7epDwuLo78/PyjHs/tduN2H2oOqqysbG5IzWaz2bjpppv4/PPP+fjjj7nxxhtJS0tr9dcNJiL5EARBaN8Knn0OgKjbfod91Oij1mlIPoJsNutmtXzk5uYybdo0Zs6cicXSMj1nn332WRwOR8MtJSWlRY57IiaTiSlTppCSksIHH3zAggUL0DStTV47GIjLLoIgCO2bZDaDohD7hz9gHz7sqHX0uqU02nXLx9q1ayksLGTQoEENZaqqsmjRIl588UVmz56Nx+OhvLy8SetHQUEB8fHxRz3mjBkzmD59esPzysrKNktADAYDU6dOZfHixSxYsIDi4mIuu+yyM2K9E9HyIQiC0L7FTkpFLs+i9tOn0TUN9LqbduheLSslNKUWyRBcPzablXyMHz+ezZs3Nym7+eabycjI4KGHHiIlJQWj0ci8efOYPHkyQMOcGiNGjDjqMc1mM2az+RTDP31ms5kJEyaQkJDA119/TV5eHiNHjmTAgAEdehIukXwIgiC0b5GWBRAPbP/HceuFjgKfby8wsC3COinNOruGhobSp0/TCVrtdjtRUVEN5bfeeivTp08nMjKSsLAwfv/73zNixIigGelyLL179yY6OpqFCxfy/fffs379em655ZYOe4LWNK1DJ1eCIAgdnT7getg5G/WGOUiyApIEigFkBUmSQVHAeRD59ZEYwjv4qrb/+c9/kGWZyZMn43a7Of/883n55Zdb+mVaRVxcHBdccAFVVVXk5uZSU1NDaGhooMNqFbW1tR32vQmCIJwJpJBYMIdgSOx87Eq+cv+9HFw/pE87+Th8nRSLxcJLL73ESy+9dLqHblO6rjNv3jxWrFiBwWBg0qRJHfrkXFVVRbdu3QIdhiAIgnCqjDao2A+vjPK3ekgymMPg6nfBXrfcXP1ACqmDJR8dRVZWFkuWLGHUqFGMGTOmxUbzBCtN0zrsJSVBEISOaP+fFwNgjLeh6yA5uxBqvRJrUhjoGurebRgOLob/64Kqh4OkI+FDBny1elCd8IMploDy1g1HioqK6vCJB/iTD0mSAh2GIAiC0EzmzuEggXNpLKXVN8Gy+i2XE6J8h0QNICGHmDFE23DleLGZM4LqhB9MsQRUz549GThwID/99BPh4eGkpaV16HkwvLqXBfsWsGXjFsLN4ViUQwmXJElISEc8PmIbUtPtUl3ZYfs23m6QDCiygkE2oEiH7hVZ8W+TFIyKkZTQFGSp4/79BUEQmsvaJwrNoxF+aRcAQs9Jwb27gkNf0RLQ2z/EttKL/ax41Ao31f9ei01px/N8dGSSJHHeeedx4MAB3n//fUJCQujWrRvdunWjc+fOHa41pNpXze6i3RRmFlLuLsenBdcie5PSJ/GPs48/fEwQBOFMIhkVdKe34bkSYsLWL+a4+wTr2u0i+WjEarVy5513kpuby44dO9i1axfr169HlmU6depE37596d+/f8cYoipD/6j+PHzNw+i6jo5+6B7dX0enyfP67fWP/VWabjtie6N6OjqqpqLqKj7Nh6qrqJqKT/ehaipZ5Vk8vORhABym4BoWJgiCEGiSSUb3doyZuDvAWbRlybJMamoqqampnH/++ZSVlZGVlUVmZibfffcd69ev59prryUkJCTQoZ4WXdLRdP+HuOHSSYC6gPg0Hy+uf5H3t71PWlgaT41+iv4x/QMTjCAIQpCSjAq+Ehcln++g0PIVbjkPXfK3hOi6BpIODT8S/Tdd09B7Q4T6LGbCAhp/YyL5OIGIiAiGDh3K0KFD2b17N++//z5r165l7NixgQ7t9Eigq3qgo0DXdZ5Z+Qxf7fqKO/rdwW96/wab0RbosARBEIKOpVs4nr2VFHq/Ji/qLSzuVGTNgv+Xo4SkSf4ht3p9XzsJTXFTk5SJ25aLnaQAv4NDRPLRDPWjQ9ZmrWV76faGDpZINOkcKUlSk9aEhvv6DpjSYR0yG9XfW7kXu8lOjK3uOl79/g0HP3pMR9SVjl/H4rI0tHwE0oaiDXy+83OmDZrG7/r+LtDhCIIgBC1Lj0gsPSLJWf0oVMHIC+YgnWD+jpqaPSxfMQHJElxTK4jkoxl+Lf6VakM17gNuOOAvkw7LBiS90ciQw7fVP9ebbjv8sQsXJZS0cPRHCnQn2h2lO7j/1/tJd6QzpceUgMYinLqazcU4lx1ALXUjhxqxDYwlZEQikiyGcgtCa0hOvont2x9C17UTJh8Nv0SD4MdmYyL5aIZVFatYl76O7y7/jhhbTNNOlo06ZzbuwAn+ck3XmpY12rdxR86S2hJMigm7wd5Qr4mGvqCHXrPxfcO2urpH3V53zOTI5Fb6Sx2frut8lvkZ/1zzTzqHd+bVCa8Sauq4s8l2ZO59lZTO3I65Wzi2QbH4Smqp+G43rq0lxNzeL9DhCUKHJMv+xVg1zYUsH38VdqmuVV5HJB/t1mVdLmNT4SbO+/I8RieN5oquVzA2eSxG5fj/85sj2hrdYscKRh7Vw11z72JV/iqu6X4NfxjyB9HHox0ori1mYe5CytxlJIcmMzZ5LFaDFTR/IisZZCSTjGT0/wrTfcH1RScIHYmOmY1Fvchd+AkGxYwiy8iShCJJyLKMLEsokowsy+iak6LKJAZowTXoVtKP+GkdWJWVlTgcDioqKggLC56eufWqPFX8nPMz3+z6hk3Fm4gwR3Bxl4u5vOvldI/oHujwgt43Wd/w16V/5ZUJrzA6aXSgwxGOofLHHyl58y08OTmoYXZ+Tq/gozE6FlsYFe4KAGZdPot0RzrV6wtxLj2AWuZCDjFhGxhL6NnJ4rKLILSCXzMLeWfxNhZlVTdrv/d/k8TZPQe0TlB1mnP+Fi0fzRRqCuXq7ldzdferySrL4pusb/hu93d8sO0DBsYO5KruVzEmaQwRlohAhxqUEuwJAMzZO4fhCcMxyOIjGGzcu3ZxYPofCBk3jrCLL2b15p+Y9FMRF2y0kLT8Bz7a8REvb3iZ1ze9zrNjnsU+MBb7wNhAhy0IHd67S/fw+HfbAOgUaeOj24ZhMxlQNf/le1XX0XTQNB1V01E1jcLKWqa+uRpVTgxw9E2Jb/7T0DWiKw8OfZBpg6fx675feW/rezyy5BEkJIbED+GGnjdwTso5Yg2VRoYlDOOpUU/x+LLH2VayjX+P/TcpYSmBDktoRDKZwGDAV1KCr7CQzt4IVOCA1cWUT/ytVQn2BGYMmxHYQAXhDBNh90+RPnf62XSNPbl+cmFW/z5qEEyt0JhIPlqAUTZyXtp5nJd2HoU1hSw9sJRvsr5h2q/TGJEwgqkZUxmbMlasVVLnsq6Xke5I5+ElDzP1x6n8a+y/GJYwLNBhCXVMqal0evNNSt99F+eCBZgcDux/+iPV5/fh374KkkOSyYjMEEm1ILSx5Ahrs/dR6i5/qsHVw0L0+WhN8/fN59WNr7K9dDtjksZw36D7yIjMCHRYQaPCXcGDCx9kdf5qvrjkC7pGdA10SIIgCEFreeYBpr6zASMqkkTDCMbGDi/SAR8Kz1yYxnVn927V+ESfjyBxbqdzObfTuSzav4gnlj/B1d9dTVJIEhmRGWREZtArqhe9onp1+BEux+IwO3h5/Muc8/k5fLj9Qx4f+XigQxIEQQha0YqL4YYc4pNTsVqtNJ0/sukEkxL+CSY1TSV7ZybdQoPr8rZIPtrA2clnM3vybJYcWMKa/DXsKN3BB9s+oNJTCcCw+GE8Nfop4u3xAY607RkVI/cMuIdnVj5Dt4huXN/z+kCHJAiCEJRKiovIMBQxedTZ9O3b96T2cbvdPPvsEiyG4LpMKpKPNmKQDYxLGce4lHGAf6KtvOo81hWs4/m1z/P48sd5dcKrgQ0yQKZmTOVA1QH+vurvxNviGZ86PtAhCYIgBJ2QpGQ+HHYeu/LKSS1f5W/k0KF+XdAm6YWuIwGqqpId14kaLbjm3hHJR4BIkkRSSBJJIUn4NB+PLnuU7SXb6RnVM9ChBcT0IdPJr8nnocUPMTN0Jj0iewQ6pI5N16FwO5Tvg9A4iO8PsugQLQjBzGMPxWmxMQ8wuP2ThjVa0aOuv8ehAv82E3rGICYa7QRTt37R4TQIVHuruemnm9hdvpvz0s6jU1gnoi3RRNuiibb6b7G2WIwnmEa3vXP5XFz343XYDDY+vPDDQIfTcbmr4KMpsHfpoTJbFNw2HyLSAhaWIAjHV+zx0WfpFt7tk84FMY6T2ser6aQs3Mj/enbimvjIVo1PdDhtZ+xGOx9d9BEzt89kds5s1hSsobS2FJ/ua6gTaYnkuTHPMSJxRAAjbV1mxUysNZaleUspri0+Yzvitrqds/2Jx8X/ge6T4MBa+PR6+N9AeKws0NEJgnAMSl2jhnq0YS7HUD/RsBZc7Qwi+QgWZsXMLX1u4ZY+twCg6Rrl7nKKa4spqini/W3vc+fcO3n4rIeZktExV4BdU7CGpXlLuaLrFURZogIdTseVOhJC4uCHP8DCf0B1kb/86ncDGpYgCMen1A1v8TUjkai/mBpcPT5E8hG0ZEkm0hJJpCWS7hHdGZ4wnH+s/gdPrXyK2Xtnc1f/uxgaPzTQYbaY+pVurQYr0wdPFxNYtaawRLhnFez43t/nIyQOMi729/0QBCFoKQ2tGCe/T/13aZA1fIjko71QZIUZw2YwInEEL6x/gWm/TmPJtUs6xKypuq7z8saX+TnnZ/5v7P8RbgkPdEgdnzUcBt4Q6CgEQTiBbXmVFFS5UCQJtS75mL2/lPySGpBAlvwzfMiShCT5kw1Z9s/7IdVtB9CacammLYjko50ZlzIOu9HOLbNv4f9W/x939r8Th/nkOh4FI1VT+duKv/HVrq+4d8C9XJB2QaBDEgRBCAqapnP5y0vx+PwXTXSAcxP4prKKbyqrmnWsnANVkBg8/ehE8tEODYkbwr0D7uWtLW8xK3sWk7tP5squV5LmSAt0aM327tZ3+SbrG54Z/QyXdLkk0OEIgiAEDZdPxePTeOLS3kzoFYem6Th9KlU+Fa1uBVtd969giy6h1j+mblVbXQcdfj9zHamTwgP9dpoQQ23bseLaYt7e8jazsmdR4a4gIzKDscljGZ00mu4R3bEZbYEO8bg0XePq764mNSyVf4/7d6DDEQRBCCql+3cQ+eYwsrUEyh3+dcF0Ttwfzu4txdP/JlTFjGvPKg7sz0EZPY0rz2/dCRzFUNszRLQ1mj8N/RPTBk3j19xf+XXfr3y842Ne2/QaEhKdHZ0ZnTSajKgM0sLSSHekYzfaAx12g5yKHHaW7eSOfncEOhThJOi6zpYDlewudhJmMXJWeiR2s/gKEYTWomj+6Ra6yAfZ4mnaIVxCP2oiEu3eTzzFsHIDACWEM1Ip5yDjgOCZPVp8c3QAZsXMBWkXcEHaBfg0HzvLdpJZmsn6wvX8lPMT7217DwBFUghTkimu0jDIChE2CzIykqT47+seS8jIjcpkyf9calRXlmRkFH+5JNeVKciSjCIbUCS57mZAlmQMsgFZllGQUWQZSZLwai4Ayl3VgfzzCSfBq2r87r01LNxZ1KT8nZuHck6P2ABFJQgdmyOiro/G1E/p0+Pk+8OpqkZZWSmau5qYhBR4JpGE8OD54Qki+ehwDLKhYbXcK7pdAYDT42Rv1V62FG3j0Z9ng6SioVHg0gAdh1VBQwV86JIHdA1d0tDR8PeRPsq91LSMRvVpvF3yv4YkHXuU+aqcfK7JaNU/i3CatuZVsnBnEfee05W7xnVhV6GTy19ays3vrCbnuYsCHZ4gdFD1LRvN6x2hKDLR0dFAXfKia3ASl2vakkg+zgAhphB6R/Wmd1RvRsVdxEcr97E1r5KN+8spr/Eyumcc52TEMLprNJ0iba0yx4au62i6hoaGXtcR6p6P1rF6TwlPTp3U4q8ntKyM+FD6Jzt48dcs3lqyB5fPv67Ec1ee3MqagiAEkK5BkM2dJJKPM0xyhI0/XeBvZtA0nU9W5/Lluv08+u1WVE0nKdzKqK5RjOoazcRecdhMLfMRkSQJRVJQUBqm3PN4ZXomRGE1KS3yGkLrsRgVvrxrJIuziskudOKwGhnbI4bYUEugQxOEjkuSqCky4fn4fXDMP3qdw8aM6D4VZMn/I7KmmLD4YmTNG3TJhxjtIgBQ6fKycncpy7KLWZZVQmZBFeE2I9cP68RNI9KICzv9k4ymqRTv24vL6SQiMZEfsmqY8fVmFv3xHFIig3tkjiAIQpvz1LBz6CBU96knDik3dCXEngNXvAJpo1sutqMQo12EZguzGJnYK46Jvfw9qnNLa3h3WQ7vLdvLawt3M6hTBGO6RTOuRyx9k5s/qVnJgVy++cffKM8/2FDWeegIomxDeX3Rbp68vE+LvRdBEIQOwWRDVY3E/eUhIqZcc9hGCSQJzemk7NNPKXrhRSzdu+O48gokoxG91oWpS2fso0cHXasHiORDOIaUSBt/vbgX0yZ0Y9aGPBbtLOL1Rbv515ydXNwvgVtGpzOoU8RJH2/dD99SW1nJVX95irDoGJZ++iGZyxdz1cBwPt4IN49Ko3NMSCu+I0EQhPZF93rB50O2hyAZTU236Tr7brmFmuUrAJBDQ0n75GMkk+lohwo67X9hEKFVhVmM3DA8lddvGsK6Ryfy2CW9WLe3jCtfXsaj327B6fad1HHSBw7BU1vLd/9+lq+efZzM5YsBmDLlEtw+lcdmbW3NtyEIgtDuaC7/dASy9eiXvU0pnRoeyzYbGI1tEldLEC0fwkkzKjI3j0rnNyPSmLlyL09+v51ZG/O4aXgqg9MiGZAcjsN29A9/16HDuen/XiB7zUpc1U4iE5PpMWI0xW4Jl1djeOeoNn43giAIwc2bmwtA8S8/Udsz9Yjt8q3XYti1A9/6TYRPvrJdrQYukg+h2WRZ4sYRaUzoFcfLv2bz9tIc/jc/C5Mi8+yVfZk8OPmo+0WnpBKd0vQf0LpdeQCiw6kgCMJhVIv/Eor7x19w//jLcet+WPIzuQtyWJG3gmszruW+Qfe1RYinTIx2EU6bqunsL6vhX7/sZO72Ambff/ZJJxOVLi+3vbeGlXtK+eyOEZyVHtnK0QqCILQPFe4Kbv7XKK6KO5/Ojs7HqKXj1Gp527qOzaVbAIiyRLFgyoI2i7OeGO0itClFlkiNsvPMlX356W8HeWvJHh6/tPdJ7RtmMfLxbcMZ/ff5fLJqn0g+BEEQ6pS5ytiVJMFZgxne87rj1p0AuFU3Qz4cwmVdL2ubAE+D6HAqtJgQs4GrBifzy9b8Zu0nyxIX9Us4Yt0QIXipus5HB0u4fWsON23azT/2HKTI4w10WILQoZS7ywEoqCk4Yd2cihzunXcvAPH2+NYMq0WIlg+hRfVKdPDZmv1kFznpcpJDZ6vdPhbtLEaSJHRdb1edps5Uf8vO4/XcIoY57NgVhX/nFPDvnAK2jupDVAvNiisIZ7r6JGJo/NCjbv9w24dkV2SzsWgju8p2YVbM/H7g75nSY0pbhnlKxLeE0KKuHpzMqwuyeX3hbv5+Vb8T1l+yq5j7PlmP0+Xjg1vPEolHO7Gr2kWSxcjUhChCDDIrK5w4VY1Sr08kH4LQXAXb4Nu7QW3ceigRpXv5vPwgxg+uIUeS8MkGDFe8xnq9lqzyLN7f9j4AwxOGc8859zAiYQQ2Y/vovC++JYQWZTEqDEuPZHt+5UnVf3TWFrrE2Pnn1f1JjTq9JZ81zU1R8Tyqq7MwKCFERY3Dbj9WJy3hdPytWxJPr1vN/EWzkdDoGdWXW/qeRTe7WOtFEJpt/yrIWw9DbgVZaVivxYCO1+7AqbqRvS4GHdwBH04hrW630pgobpjyHb2jT66PXTARyYfQ4ib2iuOrmQd4Yd4u7j6nK4p87NaM/AoX5/WKb4HEw8OatddQVbUFkykGn6+KXVlPk5p6F127PHhaxxaO1HXLB7wz7yHQ1UOF5ZPhyjdBFl3JBKE58jd9zEvRkXjK1qDXtf7q+BMQXdHRFdCNJr6IjuIyp5NBLjdG4I/j/0tkO0w8QHQ4FVrBpL4J/P7crvx77k6ueW05+RWuY9a9dmgn3ly8m8W7Tq+zaW1tLlVVW0hJ/i1Dh3zNoIEzAdi795Um9apXrCDvoT+z75ZbyHvkEWo3bDit1z1jLX8JEvrBHzLhT3v8ZVu+9C/dLQhCs6zsdjbfhIZQoNZQ7KumRK2hTK2lTHVRobqpUt0c0Gr5LtTO7xLiGJTeiTcn/4vIjEsCHfopE/N8CK1mdU4pd36wlhFdonjxukFHreNTNSa/sgyn28f3vx+D1aSc0mvpus72HX/m4MEvGsokSWHAgPeIjBgBgHPJUnJ/9zvM3btjSk/HvXMnnj17iH/sUSKmTj2l1z1jLf0vzHkUJBmQ/C0gqaPgN9+Llg9BaKbPMj/j6ZVPs+HGDcft93b7L7ez/ODyhufjkseREZXBnf3uRJFP7buzJYl5PoSg0CnSRlyYhRW7S49Zx6DIPHV5X6a8vpwHv9jIi1MHnlKnU0mS6NXz76Sn3Ut1dRaKIQRHWD9k2dxQx7s/FySJsEkXYErvjKtTJ0reeIPqFStF8tFco6ZB90mwd6m/tSN5qL8lRBCEZlu8fzGarp3wu++O/nc0JBmKpLBg/wIW7F9AalgqvSJ70Tm8/fRxEy0fQovTdZ2PV+Xyt++3YjYoPHJRT64ZknLcfWZtzOO+j9fz1OV9uGH4kWsYtATN46Hg6WconzULj09BsVqIufpSYqdPR1IC/6tBaDu6rpNXnYdX9ZIcmoxBFr/DhMC57ofr2Fy8ma7hXZskIAbVyIBVl2LwmtFlDV3W0OrudVmj3FuGJvnQZBVVUkkOT+Q3V15OfLojIO+jOefvZiUfr7zyCq+88go5OTkA9O7dm0cffZRJkyYBkJ2dzYMPPsiSJUtwu91ccMEFvPDCC8TFxbVK8ELw8aka1725klV7SrmkfyJPX9GHMMuJV1r0+DS6/+UnALY8cT4h5tY5GeRsLmbxJzupLPH3Q4lKsnPODT2JSxeftTPFhsINzFg8g/3O/QA4zA4eGvoQl3Rpv9fPhfatqKaI97a+h08/tEq4ruvgNBL2+SA8KSVoNje6KiFpMmjUPZZQfRqqT6fGXUuinIJWaWDgeZ0YeWXXNn8frXbZJTk5meeee45u3bqh6zrvvfcel112GevXryctLY3zzjuP/v37M3/+fAD++te/cskll7BixQpkcR34jLG3pBqAP53f46QSD4CKWi+S5B9htjG3nFFdo1sltrnvbCMqKYSRk7uiqTq/vLWVL/6+hntePbdVXk8IPn9f9XfMipmXxr+EWTHzu19+x8NLHubs5LNxmAPzi1E4s8XYYnhw6JGj8iqKavnw8+VcPXk8yRknXnpif2YZ3/5nPTmbigOSfDRHszKCSy65hAsvvJBu3brRvXt3nn76aUJCQlixYgVLly4lJyeHd999l759+9K3b1/ee+891qxZ05CMCB2fQZH59PYRpEbZuOLlZWw5UHFS+8WEmvnyrpH0iAvlvo/Xt1p8EfF2CnMq2br4AFsWHWi11xGCV7+YfmRXZPPfdf/lv+v+21BuMYg5SoTgoqn+0WMn2w/OW1QMQFl+DZrXd4LagXXKbduqqvL5559TXV3NiBEjyM7ORpIkzOZDHfwsFguyLLNkyRImTJhw1OO43W7cbnfD88rKk5ucSgheadF2vrprJLe8t4apr6/g9ZuGMKJL1An3G9Qpgm4pYezyuZhdVO6fbp2G+XYOjXuHpvc6R5RnFjsJr1ZJMBtB16ktL6JnlIEuE4xYN1upLKgGSuh7vka34TaKiuYiSQqSJCNJBpBkQkN6YzSKyzEdzUNnPcSA2AGsPLgSn+bj0i6XclnXyzAr5hPvLAhtqHS//3z4zX/WY/eWIKFTPwuIBGiSTIytBp/LS6UWQoUhFoCIsh34qodiCg8NVOgn1OzkY/PmzYwYMQKXy0VISAhff/01vXr1IiYmBrvdzkMPPcQzzzyDruv8+c9/RlVVDh48eMzjPfvsszzxxBOn9SaE4BMVYmbm74Zx5wdrufW91fw87Ww6RZ142t/aFDs1NfCbLTnNfk1ldxXK/mq0OCvKgWokb9PuTNea12OR/L8G7PZSBg3+AS+wbfvRj5eYOIWeGc80Ow4huMmSzKT0SUxKnxToUAThuCL1Ymw1+UQaq7BGhaLruv/Hlq6jqXCgKoR9tTHIaERQwpCQLdh+egeD6iJ7+At0W7YUQ2RwrhTe7NEuHo+Hffv2UVFRwRdffMGbb77JwoUL6dWrF7/88gt33XUXe/bsQZZlpk6dyrZt2zjrrLN45ZVXjnq8o7V8pKSkiA6nHYTT7WPEs/O4dXQ690/ofsL6bk3jnhVZfO+uAWCIbuAfgzsTazUBIAFbypz8vK+UfTVu3JqOS1UprfSQt+rQarqWcDPPT+7HiOQIPl+8hafm5/Hj7f3pnHioL8nSZf6ZAbt1fYP4+H7oulp309i0+Q7CQvvRs+ezLfjXEARBOHmVP/7Igel/IO6vfyHy+utPWF8tL2fn8BFNysw9emDp1YuQs8cQNql1E+5WG+1yNBMmTKBLly689tprDWXFxcUYDAbCw8OJj4/nD3/4A3/84x9bPHihfRj7f7+SER/KqzcMPulrl7vLa7hrZRYbDSqSphPrAZsikydpuE11XZVUHbS6myKh5Ndi3Fre5Dgmg4zH579u+nj/GkYNGUBSUhI2m42cnGVk774RVbVw3sStTfZbsXISEREjiN85mLwHH0QyGkn/+ivMXYO7E5cgCB2HOzub3RddTGlcNDmJMf5Lz/qRl6DRD5W40DFoOnqtCxkdSQdJ91+mkc1mzn32XyRl9GqVeNt0kjFN05q0XABER/t/Xc6fP5/CwkIuvfTS030ZoR17YEJ37v90A8/P3cUDE0/c+gHQOdzG7PP7saawkn9szmUrbgpVlU7IjHOEck6cg9+/u5aYEBO/HZnG6G4xdB5vo9arUlrtpazGQ0Glm/1lNWzbW8C2rVs5sLuAmZn+JCMqKoq0tDRsdlCUI6d/l1eXQVkmeTM/BkD3esm68mLK/uPALRWTlHQDGT3E5UJBEFqPMSWF8KuvIvvAHvKry0m2hIAk+ft9HO1ekggBNF3HGGFAR0erS0z2Vvone8zbtaPVko/maFbyMWPGDCZNmkSnTp2oqqrio48+YsGCBcyePRuAd955h549exITE8Py5cuZNm0aDzzwAD169GiV4IX24fKBSWzILee/83YRYjZw7VkphJ7kENwhsWF8Nr7pwkkFlS7u+3g9tR4f7948mrToQ4vS2c0ydrORlMhG/UtGpQPD0XWd0tJSDhw4wL59+9izZw9JybE4HIUsXTYWszkeWTYhSQqhL1agsa7hEGGXXEJ+0Te4pWJUr5ntK7ex8r0ljLu+J8kZESiKGEouCELLkk0mEp58kpAP3iJy3Wqm/OfVUzpOeUE+b933OwAGX3RZS4Z4ypqVfBQWFnLTTTdx8OBBHA4H/fr1Y/bs2UycOBGAzMxMZsyYQWlpKWlpaTzyyCM88MADrRK40L7cfU4XnG4f/5i9g//N28XNo9OZNr7bcVe8Pdy+khq+2XCAVxdmYzEqvHHTkCaJx4lIkkRUVBRRUVH06+efCry45BJcrvXU1mzH4y1F0zyga+jJdpRaE6a4BDy5uVR+9x21d2q4KxLZu+APqO4wtqZovLEhm+odMv1Sw7gt0cro2Fgw+EdNeDylGAyhyPLJJVqCIAgtzetx8+0/nwJAMRqRg2ANGBDTqwttLL/CxTtL9/Dmkj0MTo3g0v6JjOgSRedo+1H7g9R6VL7flMcnq3NZu7cMoyJx04g07hvfDYe1bU7quqbh2bOH0k0/sWhvLgWZ45k5bDF7UycTUZFHenEkJVFu9oY7eGbXf7jx5ucxGBzM/7VbwzFSO91O164PtUm8giB0LD++8E92LFvE9I9nNWu/3etW8/Xfm14efuCjb5FbaTkJsbCcELTiHRZmXNiTMd1i+M/cnTw2ayuqphMbamZU12j6JjkwGWSq3T72FFfzw6aDVLl9jOkWzQtTB3JORmyrTb1+LJIsY+7ShYQu93JefjVf/HM1PYsvYF+KTkZeBJFOlc7W1ewNn8BuawpFb/Ygp5MNzCZk1YykK5grOqH7NCSDuDwjCELzbF+y4JT22zjnx4bH0z78GoMxeFphRcuHEFBOt4/VOaWsyC5h8a5isouc+DQdm1Eh3mHh/N7xTBma0rQPR4B53Sp7dpTyYlkpc3BTpmsk+cq5Je8r7t7zHhJQbbFQVv7FEfuGnZ9K2Dmd2j5oQRDarVn/foZdK5cx8fbfA6BpPgp3Z6OpakNHUz8JSQIkicI92RTszmo4xvXPPE98l9YdrdemQ21bmkg+hPZG03Xk+n/87ipcu74hf2cehlUj0dAokCrQJP8/MwnITinnipunYLGI6bwFQTixDb/8yLy3Xj6tY0iywn3vf9GqrR8i+RCEIKBrOh+99yG79mYfsS0mJoZ77rknAFEJgtAe6bre0MKRs2EtXz77GLf+9w1CoqLRdQ00HV3X/LOgajqapvrn/9B1slYvZ+6bL3PhvX+g55hzWi1G0edDEILArrzihsRDsjpQDAYcdisl+ftRVbV5B6sphcyfoOogOFKgxySwiORcEM4UR+uQLxsMJ9WSYTD5R+At++IjOvUdgD08osXjay6RfAhCC8qvcPHTloP8sOkgW/YWcm3dlRVPrZMa3UhFtYvOcXGkp6ef/EGLdsLb50FtOVgjoNY/WRC/mw/Jg1v8PRxPTU0O+3LfxunMxKDYiIo+l6TEqciy+CoRhLZSWVIEgNd95ASJR9NrzDnIBgML3nuDt++/g34TLmDkNddjNAVuMUVx2UUQTpOu67y9NIdfNuURv6+aQZKBuBAzIZ3D6XthFxwOfwbyzI/b+XLtftb+dWLzXmD5SzD7EZjyAaSO8reAfHs3JA6E2xe0/Bs6Bp/PybLl45BlMxHhw/D6yikpWYjBEM7Ys9e2WRyCcKZb8M6bhG8MwaLYkBpNcKjj71dmGBFBlytGHbHfkk8+YOXXnwJw7i13MvD8i1s0LnHZRRDaiK7rjPjvQvLznTyGlXOwsEVXcTs99NlYStXGUgYanagSSB6NqWedwkiXPpNh3fvw6Q2HyqyRMPUT1KoqatetQ3O5sWT0wJSaCoC3sBC1tBRjYiLKKSbxNTU1bNiwgcLCQsxmM126xOD1VhAdNY6IyJF4vf7kw+crP+YxdF0HDSTl5CeTEwTh+M46fzKlmVtwW1zUhtQCdf/WgIiSSFipsWf53EZ7+P/9JZHIlPSH8GkeDDExbR12EyL5EIRTUZkH62eyc+WHLKg9gMXiJd/9IhqwN7yKJZa+DD7or+rrZEeV4Nz4cB47v/lrKmi2GPYMex7XjgVYpRqieo/E0e98nIsXc+CB6Wg1/hWAdUAfdhY+nxdl3QYUXQdZxnHlFSQ88QRSMyYW8ng8vP766zidTuLi4qipqWHlypX07TsZq3U1xdsfQpZNxMScR4/ufztif92nUfHTHmrWF6LV+FAcJkJGJREyJumkFxcUBOHozHb/1AOJ1w7GmhHZZFvu/HVU7Syo+3dW92+tbrSd6vUSnmvCIJuISWjGpd9WIJIPQWiu5S/B7IfBaCOky4W8KU9mSFQU8VkbsOQM5rKyvlwGuEKNZJ8Tz/+6OJgYFYbdcPInf13XWVuwlu0l29jy889YtpQQK0fic7vxzVrP4IsOkD5/KUpEBGmff0ZpjZNZj8/A6SoBQBnYjbPGTqRLZS2lb72NJMkkPPk3NLcP3a0hhxiRjjO1fXV1NeXl5QwaNIgBAwZQXV3Np59+yubNFiZPnoemuZEkI5J09EnTnCsO4lx+kNCzkzFEWXDnVFLx4x7USg/hF3du1p9bEISmNI+/w7ruObLjesq5g+Dco+9Xs7GQ0o8zAZB8rRbeSRHJhyA01+yH/fd/yCTJEsa9Pg98cTMc/B7d9CYaDngwCznESNdT+JWv6zrTF0xn7r65mGQT3kgP+ji4vuvZ3JI0lQ8euo+1P3zDgCm3cvCRR9h9+RWs7RSLz6QwNLcUjxTC9sQQls//GVeBjwQgZPxFFL2xCXd2BQCyzUDYhFRCRiYeNYaIiAjOOeccFi9ezLp1/gX24uLiuPrqq/37y8fvqKaEGkHTce+tRHV68B6oAsAY2zKTxe3eUETmynxqKjyERlnoMzaJxK7hLXJsQQh2ukcDwBBx8nMFOVfkUf5NNpbeUURNzQj4bMuiw6kgNNcXt+Jc/y2vZQ3HbJLoG17AqsI4dvSN4fyBU4hOSGNEn65YTae2fkKFu4LRn4zm4s4X8+ez/swP77/Is6ZPAPjtj/4+HZc9+Be6Dh2Oe88eqpctY9P2zazdtQVLSDTuWgVdLQDA7LiTLn3iGRYfiiuzDMcFach2I5Vz9+LNqybqxl5Ye0cdMxaPx0N5eTkmkwmHw9GsSyY1m4qoWV+I6vRiiDATMjwRc2fHKf1NGsteX8jPr20hvrMDR6yVon1VlOZVM+76HvQek3TaxxeEtuLxFFNSshjQ0NH91079F1Drnut1z/0l/gc6vpIaauZX0O36u08qoffkOSn9eAfIEnH3D2q1S5+iw6kgtKbJb1Kkdsa3exX/d8sTGGtrMa8qxueUmbfYB2TBZ1l8cecIhqRFnvBwh3OYHVzT/Ro+2/kZ3+/+Hkz+8jvir+eSv1xAYrcMjHWzo5rT0zGnpzNW10nbuI7vXphFSCQMmHgJ3YePY+Zj69i9rZLRA+KpWVeIc+VBFLsRb141AIZY63FjMZlMxMbGNvs9ANj6xWDr1/Kd2pxlbiRZIjkjAkesFYNJoTSvmuJcZ4u/liC0pn2577B376snUdPff6O+H4euadBfI7niMoyx/gUsfWUuvAecqJUe1Eo3aoX/3ldci1rhQYkwE3lNj6DpcyVaPgThFG3dv5mf57xB791budM7nd+EzmGCdQPETuTGLQMAyHnuolM+/u6K3WSWZmJWzAyKHUS4JfyE+6z5KYeV3+5uUtZrdCLjru9B7ZZiXNtK0dwqxjgb9uEJGBxHv3yi6zpVVVVIkkRISEibfGHpuk6JV0VHJ9poOOZrql6NpV9mkbkyH0+tD1uYib7jkhk8KTVovlgP56p2svCDt8leswJPbQ2RyZ0YceW1dBs2MtChCQG0c+eTlJYt5ayh33EouYCmycaR8pZ/x/ba+zmr20+EpnSn/MfdOBcd8G9UJJQwE0qYGcVhQomwYO4UhiUjstVHnYnp1QWhjZQsfx3Dz48z2fMYWXoyBnz46hoU/3ulj0uHXnLMTpmtpaKohvzdFRx0e1GTbHRLDKWT1Z9kuN1uKioqsNlshISEHHX/nTt38sMPP1BR4e8fEhkZyWWXXUZq3TDe1rCszMkfM3PJrnUDkG418Y/uKYyJDD3mPrquo/o0DEalUZmKqtagKG2TMJ2seW+/wrZFvzLowkuxhjrYMPt7yg4eYPKMJ0gb0LYTxQnBY978LgCMP/fIJRiOJ3/LbLYW3t3wPGXVI8T2HUfo2cn+zuQB+uyLyy6C0Eak/peydtu7PFf1Brtr43BVW4mWKtDG5GF1uvB4hmM2x7VpTDVhBu6RK9mi1sK+UtgHZ4XZ+F1hNhtWr0bT/J3VUlNTueqqqwgNbXqC/+abb4iOjmbSpEnous6nn37KO++8w+OPP95qMT+wYx/hRoU3eqchAb/bmsPVG7M5OK7/Mb9IJUlqSDx8vmp27nyCgsIf0DQXRmMkKSm/JS317qBIQiz2EHweN6X7c7GGVVJd7p+l1nyMBFA4MxgMsfh8hfzww8T6Hh1I1GK25KPrMh53KJJsQ6LuB0zdZRdZcmFoNKu6Y2QXHKPS29V8OiL5EIRT5FN9DJ77HlLkeLTYKDzmnmCI5jJ5DldpbxAdPb7VEw+vt5KSkgW4PYVYLElER41lZl4lmdUu3umTRobdyqzCcp7dc5DiKo0nRoyge/fuVFRU8NVXX/Gvf/3riKQiPj6enJwcli9f3pConAqPx8P27dspKSnBarXSo0cPIiOP3gemZ4iFeSVVvHOgmFP5+ty//z3yC76jc/o0rNZkSkoXs3v3v1F91XTt+qdTfg8tZfjkqZhtdrLWrKQsP4/Og85iyCVXEpfeJdChCQGka7dRXPwRYaF2kEBCB8mGz2dFVVOQ5FrQdbRGnU91NFR0SkrthIUVU1jQlfG3jA30W2k2kXwIQjO5vW5mzJ/BnPw5hACaHIakVSGhoyNx2xXLGRT251aPo7o6m7XrrsXrLUVRQlBVf4fLoT1nIUtwz/Z9xJkM5Lo8AAwrzGVNdhn79u2jsrLSXzZs2BHHvfbaa1m3bh379+9HkiT69+/PgAEDmhWby+Xi9ddf///27js8qjJ9+Pj3TE3vvZFAQggl9BKkqUhzFcGCrl3srrq76Ko/u7sKLnZdWXzVtWIXK4L0JiVA6DUkISSk954pz/tHIBBqCEkm5f5c5nJyzpln7jvDnNw55ykUFhbi7u5OVVUVixYtYty4cQwffmo/h//2jOSzrAI2FNd1hH0hOoSbQvwafdXCyTkcpWrJy/8dJ6cwSku3AuDhEX9ecR9TWVnJ6tWrSU1NRSlFaGgoo0aNwsvLq0nt6Q0GBl0xlUFXTG3S80XHZLGEk511BdOue7jRz7Hb7axYsYJNiasAcHJyIjc3t8kdwx1Fig8hGmlfeg5Pv/c9IYZclkYtrt+us5fWP+7t25MBHq6tEk9+/lIslmLi49/D22sYubkL2LP3cVyPPMeqIZ/xa14JebUWujibmRzghX5gV5KSkigsLCQ0NJRevXoRHh5+Srsmk4lhw4ZdUGy5ubkUFhYyevRoBgwYQGFhIR9//DG///77aYsPJ72OO8P8uTOsaaNjggKvQK9zJjvnJyyWQny8LyI07EY83Hs3qb3vv/+ejIwM4uLi0Ov1bNq0iS1btvDUU09hMMhps7OxFhVRtW0b+hNvk51YGJ9SJGunf3jSc7KTkykqKiJ11aq6fZoOTTt6nHa0w6lOh1Z3WQSAzMpKVq1aVd9MdXU1RUVFUnwI0dEopZiflMmzP+6kzBoB1ghij2gcCfkGAH9nf7p5dWNa7DTGdhnbanEFBv6JzCNfsH373fXbdDpnevd6CycnM/dHnHQyMnowenTLXp61220UZ2fjjCIurgcrV65k5cqVQF1Rc/vtt7fYa/v7j8Xfv3l+/rW1tZjNZjzc3TGaTPXbqw8cwDksDL37mTvCio7nQELLjEo6eP00AD5etuy8nmc2m7npppvw9PTE2dkZo9F47ie1MVJ8CHEWxZW1PDl/J7/uyOKqfiH8fWw00+asZl/JQCLLorjYJZVnn3rGIbE5OYUwbOgiiks2U1uTh5NTCJ6e/dG0pk1udqHSd27nt3dfo7wgHwCziyuXX38rXl1jcHZ2Jjg4GP15rC/jKKV5eQRkllBSXszqwpUoTeFTU83AVWs4/OVXdevlXHUVwc8/h9YOT/riwkR89BGGBlcZThoweuIA0jM8VqpuQrEb83Ipq6jAx80NpVT9dnWsf4dSYLdTtW07xd9+C4CrkxP9lyxuEx2pL4QMtRXiDH7dnMED32zD09nIS1P6cHl8MADJueWMfW0lQa46frhnEEEBjl0dsq345NG/gKYx+qbp6A0Gvnq+rt/LQ59+h9F09unY2wplsbH/hUW4WtyP9uCpO8GvyfmegRfFETpwMBVr1pL/n//gMWkSoa+96uCIRWuw5OaSPOr4VcO4vXta9fXL16zl8J13oplMdFu8GGNg27zFIkNthbhASike+GYbAE4WO/asclKCyvl0wyEW7swmNtCdL+8ehrer6RwtdR4hPXqx7fdfWf7xe+hPGAeo07X9qx3HVKaW4GpxZ3vRajKNhQR5htLfNogRgVMp+PxpcpeuoOZg3ZwMnlOmODha0VrKFi6sf+x77z2tH4DdhvctN1P0yackjx5NyKuv4Hl50ycwbAvkyocQp1GRlEvqV3tY092dBWn5bK+1oANcDTqig9yZe8sgAjwav6hTZ6DsdvZv+IPDu7Zjt9sIjo4lbuTFGNrRrYlf395K+KESfE5adMswBLSD67HlF2AMC8NzyhRMYbKOTGexp0dc/ePWuuphyc2laksSJb/8TPmSpQ32Bb/0El5T217xK1c+hLgAtrJain88iI+rmam1eq7y8GFHfjnLsTDVaqJ7j3A8pPA4habTEZswgtiEEY4Opcly0suoDXLDa4A/qqSGzcsyyLMo7pl6CTDS0eGJDsheUUH+e/+P2pSD2CsqsVdWYsnOxpqdDYApuhvBs2biNno0talpmCLCMfj5OTjqCyfFhxAnqdiYjaq2ooDaCgsAceiJQ4/Ow4Tr0GDHBtjGKaUoLk6krHwXOp0ZH+/huLhEOjqsRrn4ph6smLePn79OBsDNx8ykW+LO8SzR0cWsXsWBkaMAqNq5C+fevZqlXVtZGSlXTsaalYXe2xvnfv0wBQbiMngwTr164ty/P8bA4xMVGry9m+V12wIpPoQ4gb3WRvn6I7j088cU6YmqtVGyIPX4/tJaShal4XFJBAafznf1Y095Fb/mlVBstRLlbGZqoDfexuOnEaUUO3c+SG7eb+h0TihlQSkb4eG30z3mKQdG3jhRff2J7ONHWWE1aODu49TuRxWIC2fwP96pvCb5QLMVH/bycmzFxQDYioqo3r2b6CWLO8UoKik+hODoiqp71pOx5jtqI7PQu5nRlRjQ7HoYpQO7DlteLZrSQ6lG0daFgJ7Q0Btwd+9JaMg0R6fQ4n7PL+G2Hal4GfX4m4y8n5HPkwcyWTEklh6uzgDYbOXk5v1GYOCVxHZ/DoulkHXrx3L48P/aRfEBoOk0PPycHR2GaEPK16ytf+wxfnyztWsMDiZm9WpyX36Z4m++wRQejlKqSUsMtDdSfIhOTSlFQcEKUlJfp6xsF7ouzpjLw7DZjKDsKM0Omh2ls6H8bSi7FaWvPfpsG5mZnwF0iuJjdVEZTnodb/SIINzJxP/LyGNeViHzc4p5omvdL2uDwZ2w0JvJyPyUnJyf6p8b2/15R4UtRJPZyivImTWTkm+/A8Dj8svROTdvYaozGanavh33y8YS9vbbzdp2WybFh+iUlFKs/eM2amrWNNheowxUu+bWf69p4OLigk6zU1Obg7tbLxQKg80Nnc5IRcWB1g7dYe4M82dNUTm37Dh+G2pqoDePRQU1OC429jnCwm6hvHw3Op0ZL69BGI0d51616DySR4/GXlGBzt2dkJdn4TZmTLO2X7FhI9n/fIHa1DT8//bXZm27rZPiQ3Q61dXVfPvttzi7HMDLC+z2EDR6odDQ6+vWjQRAQVZ2Nl26ROLrp8dur0GnM2EweNStu4AOL6/B2G01Ds2ntXRxNrNscCzJlTUUW21EOpvwN53+3rSra1dcXbu2coRCNC97Rd1Chx4TJuB+ySXN1m5lYiJ5/3mXyvXrce7Xj6jvv8MpNrbZ2m8PpPgQnYrNZmP+/PlkZGQwdepHdO/e/YzHWq1W/vWvf+HtNYAxo688Z9t2u2LVgTx2HSnFbNAxIsaPHkEda64aTdOIce18HW1F5+QUH0/1nj34XeDEYjXJyaT86QrMcXHYCgux5uRg7tGD0LfexH3sWDSd7tyNdDBSfIhOw2az8e2337J//36uu+66sxYeJ0pPTz/nMUop7vxkE8v25uLlYqTGYudfv+7h6gFhvHpd3wsNXQjhAGFvvE7qddNIHjeeoGeewXvadefdRtGXX5H93HMAWNLT8b75JlwGDMB15MhOPZKq85VbotNavXo1+/btY9q0acTFnXvuhmNLp+fn57NkyRLy8/PPeGx5jZVle3O5sm8Ii/46ih//chEA323JaJ7ghRCtzhgSQuTnn4HNRs6//nXezy9btpzsf/4TjyuvIGbdH8Ru3kTAX/+K26hRnbrwACk+RCdy+PBhYmJi6NGjR6OfEx8fj9FoZM2aNfz8889nPM7dycg9o7vy07YjDH1pKeNeXwXAG9P6XWjYQggHMnXpgiE4GGWxNJhm/WSViYlkv/BP8t75D/bKSgDy33kHl4EDCXnxxQ41QVhzkNsuotM4ePAgQUFB5z7wBFOnTgXgnXfeIS8v76zHPjExjlsTItmTVYrZoKdfhBduZvmICdGeKZsNa1ZW/ffZL7xA1Y6dWAvycRsxkqBnn6Fy82bSb7sd7HYADH6+eF9/PZrJhM7NrVNMGna+5MwoOpXso+slnC+j0UjPnj3PeVyIlzMhXjJBVWspKK/hp21HSC+sxM/NzKQ+wUT5uTo6LNHOqdpaKtat4/A9956yr/S3hZhjYrAeyaL466+x5udTsXYtzv37437ZWHJnvYzlSFZdkbJtG373ndqGkOJDdCIJCQls2rQJu92OrhP2Lu9ockqrmfTmaspqrET4uJBTUs3sRft47oqe3HZRlKPDE6dRVlhNTaUFZa/rpF3/f1X3f07aVpJbSUl+NWE9vOtm/dTqRlxR99/RIe/Httc90LSj20/uUqEd+5/W4HuA4pxKKktr0Rt0GIw6Ct56A8Oh3Xgd3R/6xutk/vVvAIS99SbV+/dTuXEjANV79+B7551433QjmqZRvmIlhf/7H3pfX/wfehDfey5spExHJcWH6DRiY2NZt24dOTk5BAc3bnG4rNIyUopKKFQQAlRYbaRV16Jx/NylO3oCPHrOQwN0R0+CGuBl0ONplI9ac9uRUUJBRS1PTOzBpXEBHMgp577Pt/Dcz7ul+GiDqsstfPJ/fzTpuVsXn3vEWXPQGTTsVgU+E8BnAiFHVjMkupSyE5a013l44j1tGgZvb5TNhvu4cejM5vr9XT76X90U6Z28Q+m5yBlRdBqhoaGYzWYSExO58spzz9sBcPnabRxxcoPYoUy2lfPpzlRWFZWf92sfHt0Xo05ORs1pZHc/JvYOYuZve5n5214AogPcmHfnUAdHJk6nurJuhejhU6PrrmToTriKcfRKhaZpDbZba+xYLTac3U3AsasjHH0MUHeF5Pi2k74/YcLAY1T9Y9Xge08/Z0zOBpRS2K2KX97aQgYjKVw0A4OtGs/Jk/F/+CGMISEAeEyadMZcpfA4Nyk+RKdhNBoZO3Ysv/76Kx4eHowaNeqct1+OOLnVP/5R7wZHC48FA2I4do5TgF3VnebmZRXwdXbRKe3YUdAplotqPWaDnjk3DSSrpIrDhVX4uZmI8nOVE38bZbPWdcYMjvbEP8LdwdGcmaZp6I0aJYW1RMb70e2eD7EVFuI6ciQ6k8nR4XUYUnyITmXQoEFUVFSwYsUKkpOTmTRpEiFH/5I5k2C7hfgAXxbllwJwf3gAAzxP36lxe1klP+uKWTb4+HBeT6Mes/QxaTHBns4Ee0on37bObq27xKA3tI/Pgn+4O+m7C9jbLYpeI3ujO8NSAqJppPgQnYqmaYwZM4auXbvy008/8d577xEWFkZISAgBAQGEh4fj7+9ff0UksKaSHpqNj/s0bp0SmwKDphHlYj73wUJ0IseufOgM7ePK1KW3xbHhxxTW/5jChp9TiIjzIaKXL137+6PsisrSWvzD3dHkdmqTSPEhOqWIiAjuu+8+du3axZ49e0hNTSUxMRGlFO7u7gwZMoQhQ4ZgVIrOsWycEC3LaqkrPtrLlQ+Tk4GR07ozYHwXkjfnkrI1jzVfH2DVl/vrj+k+JJDL7ujlwCjbLyk+RKel1+uJj48nPj4egJqaGo4cOcL27dtZsWIFSUlJaFHx1J7HydKgadhaKmAh2rFjVz7aS/FxjKuXmb6XhtP30nAKMsv58p8b6/eZneVXaFPJT06Io8xmM1FRUURFRTFixAi+//57qK0hy+yJTSn0jejIqNfAalen3acsFmozMqhNTaM2NZXatFRqkg9iycwk7D//wblP7+ZOSYg2w9bOrnwAVFdYWP9jCqX5VZic9FQU19bvmzJjACExXo4Lrp2T4kOI0/D19eWOO+4g549NvGs1c+fONJ7uFkLXc/TlMACupSVUbt5MbWoqNampx4uNw4fBagVAc3HBFNkFg48v1txcLFlHpPgQHVr9lQ9j2y0+lF1RkleFpabu+uXGn1NI31VIZF+/uu3VNsbeFkeXPn44uUoH1AshxYcQZ6DX63lq5FAG55fw1z3pDN+wh4u83Lgq0IvhTkZy8/LJ37uPygPJaKkpuKWn0SMzg+8rKzgEoGkYQ0IwRUXhOmIE3lGRmKOiMEVFYQgMRNM0rEVFHEgYTuZDD+O0ZAmmsFBHpy06IGWxU7byMFV7C1E1NoyBLriPCccU1npDXu31t13aZgfNouwKvn9lC9XlllP21VRamHB3bzz9XRwQWcckxYcQ5zDez5Mtw3vxc14x32QXMjNxF989di9eUD/9ck5YBCYNii4bD0MGE9+7J6YuEeicnM7YrrJaKf3f6/Xfa6nLoMybo7MsUTf7kg7sFvDqAkFyZUQ0TcnCVMo3ZOES74/O2UDFxmyqdhYQ8FB/TCFu526gGdiODbXVt80rH5UltactPJzdjWTuK2br4sOM/nOsAyLrmKT4EKIRnPU6rgvy4bogH3KjAsjpEonhUFr9/sDsI2C14n04HUPiOgoGDsJz8mTcRlx02vZqNi0n67G/U5VZhXdMBQHxZeiW/uXsQTxbzKkLVghxbspiRzPo0Lmb0LsY0Mx6lMWOOtoPozXYrHZ0eq3NDk0NjfXm4pt7kJ9ehpuPE2YXA1aLnYNbcqmuKCWqr5+jQ+xQzqv4mDNnDnPmzCEtLQ2AXr168cwzzzBx4kSgbsXQRx99lMWLF1NWVkZsbCxPPvkkV199dbMHLoSjBHh6ELDoNwBs5eVUrFuHNScXp149sebkULV1G2XLllG6YAHd165B7+VV/1x7eSn5T99NwaKtmDw0usx6GJfx1x+f41kpUHagbpEt3hkENaXQ7RIoSgXvKClAxHnznBgFGlQl5WKvsWEMcsXjuljMXTxaLQa7TaHTt61/u9ZaG2u/SyY7pQRlV3WfLQXlRTnUVNb1zwqM8uCKh/oS3sPHwdF2LOdVfISFhTFr1ixiYmJQSvHxxx8zefJkkpKS6NWrF7fccgvFxcX89NNP+Pn5MW/ePK677jo2bdpE//79WyoHIRxG7+aGx2WXNdjmMWECXtddS8qky8l46GG8b7ge15GjqFr6DdkvzcZaZsNvQm98n/9/6Ny9z/4C41+CZf+Eg8vgrf7gFgT3rwOX8zsRVlgq+OPIHxRUFRDqFsqw4GEY9dJhrrPQORvwnhIDUxwXg92u0LWxqx55h8vZuTLzlO1DrojCP8KdgC4euHjIlOotQVNKnX5cYCP5+Pgwe/Zspk+fjpubG3PmzOHmm2+u3+/r68vLL7/MnXfe2aj2SktL8fT0pKSkBA+P1qvKhWhu5atXk/fGm1Tv2gU6BXYNl4AagkabMPceBGFDYOi9YDjHya2yEOaOgpLDENwXpi8GQ+NnUE0pSeH2hbdTWF2IXtNjU3U9+RdMXUC4e/iFpChEo21ZdIgtvx/izldHOTqUesquSFyQRtr2fPLSywDwj3Dnuv8b7ODI2qfz+f3d5J4/NpuNL7/8koqKChISEgAYPnw4X331FYWFhdjtdr788kuqq6sZM2bMGdupqamhtLS0wZcQHYHbyJFEffct3ZYsIXBcOKHDC4m4PQ5zzwFQXQpLnoXXe8KPf4GDy8/c0KE/6gqPhL/APavOq/AA+D3td0prSpk7di6bb9rM40MeB2DmhpkXkp4Q58Vua3tXPjSdxpA/RdFvbF0RPubGWK7+x0AHR9U5nHeH0x07dpCQkEB1dTVubm7Mnz+fnj17AvD1118zbdo0fH19MRgMuLi4MH/+fKKjo8/Y3syZM3n++eebnoEQbZwpLBSfNxafuiNrG+z4BvYthKRPodulMP5FCIhreFz3CdBrKqx7B3b9AEPuhBF/a/TrT4icwNf7vuaeJfc02P70sKebkI0QTdMWb7scE97TB1dPEztXZRIzKLBdTYTWXp33bZfa2lrS09MpKSnh22+/5f3332flypX07NmTBx98kI0bN/LSSy/h5+fHDz/8wOuvv87q1avp06fPadurqamhpub46hmlpaWEh4fLbRfReSgFe3+FxU9DURrEXVHXsVSnrxtqW1sJeXs4kL6aqWHB9U8bGzGWx4c8TqBr4DlfospaxcasjRRU1/X5GBg4EINOBruJ1rP+x4Ps25DNrS+dfgSYoyhVt0hc+q4Cln2yl4tv6kHPEWdf6Vqc3vncdrngPh9jx46lW7du/OMf/yA6OpqdO3fSq1evBvujo6P573//2+zBC9GhWGth80ew7QuoKgJlqytMDGaKPcNIc/fh5tJN9Yf7OftRa6vl0cGPMrnbZDQHjYKx222snvcxWxf+glJ2NE0HOg2NumGVmqarm7JE09XFqGlomoam06EB6Oq2H/+6gON1dfOjHHvduulSTjr+6IrF2tF2QDv6OnX5xF00hpihwx3xo+zQ1s1PJnlzLjf/q239bFd9uZ8dKzIAMLsYmDJjAL6hrTP3SUdzPr+/L/hPH7vdTk1NDZWVlQD1S5Efo9frsdtbbyy5EO2WwQRD7677Aiw2C+9ue5dtedtIzE6E0hQAPM2efDT+I/xd/Hlpw0s8vfZp5h+Yz1PDniLGO6ZVQ66prGTB27NJTdrM4Cun4ubrVzdkUdnrRg0rO6ruAUop1NFzgbLXbT/2BQplVyhlP37ssX3KXrev/phj7Z3c9rF2Grbd4PhjxxyNRR2L5Wg+OQcPYLfZpPhoAXVDbR1/O8NuV+xYnkFOWikh0Z4U59b97rr8gXhCY70xmvQOjrBzOK/i44knnmDixIlERERQVlbGvHnzWLFiBYsWLaJHjx5ER0dzzz338Morr+Dr68sPP/zA4sWL+eWXX1oqfiE6rB8O/sD7O94H4MmhT9LNqxvRXtF4Ox0fnvvyqJeZEjOFF9e/yNU/XU28fzxjwsfQz3cY4W7dMOn1eLkYG3VVxG6zs39jDk5uRnyCXdEbdej1OgoyywmK9jxlZsqS3Bx++PcLlObnMeXxZ4nq1/476s1/+XnqL4G0Y8pux2ptOFundnJeJ/2bOPWfyMkbVN10NKquEORoQVhX2B3dbz9eFB4vAuuKvqqyAsoLc0nflUJtVU2Dl6iLTYFWd7GvPhal0DSt7nXOGKs6fuXq6HO3L1+LzaLoPnQQ3Yf1wWg6Pqw8+2Axa745AMCBxJz67TuWZxDQxUOKj1ZyXrddpk+fztKlS8nKysLT05P4+Hgee+wxLjs6z8GBAwd4/PHHWbNmDeXl5URHR/PII480GHp7LnLbRYg6Sikmfj+RnMocZo6cyYTICWc8ttZWy8K0hby26TUKqgsAsFu8qEiuG9kS6uXMHSOiuLxPMEGeDad8t9ns/PeBFY2Kqc/FYSRc1Y3c1H38+OqLmJydmfKPZ/ANi2hakm3M97OeQ28wMPmRpxwdygX55Y2X2bdutaPDaBs0MyaXWND1wuQaSlQfP4pzqygrrD5lOvWALu5MfXSgdDhtolbt89HcpPgQ4jiLzcKTa5/kt9TfuL337UyInEB37+4NOotWWavYlL2JL/d9yaqMVfg6+WKzGbHnTybzSNQpbcYFe3BJD38ujQukb4gnnz75BxUldUuFX/W3/lSVWzA566ksrWXpR3sI7uZJUFdPsg4Wk51SNxTeWvEVgV29uHLG/+Hi4dk6P4xW8P3MZ9EbTUx+5ElHh3JBPn38YZxc3eg9ZmyD7ac92Z/0K+BsvxJO7IODdvRayrHv0epuu9f3tzmx742G1aooya1C03QYzUbqL1Wg1celqaMxHtvF0UlH6zcej7lu97GdR9s4IfSu/aM5tHM/e9duIH37QgCMTgG4+o6gujLyjDlOmTGAkBivM+4XZybFhxAdiF3ZmbttLv/b9T+qrFWYdCb8XfzxMHlgVVYOlRyi1l5LpEckD/R7gHGR49BpdX+5KaXYk1XG0j05vLp4PwB/ig9mbXI+RZUWQj2d+fOhute5/d8jzjqbo7LbmfPAcpTSCAhPZ+pjN6I3dKxZUr998WlqqyoZfMXxJSEaXPI/5Rf1yS2oE/adtPOE7099mqrfr044Vp30//pbHkcPPNZfpuH3sO67L+gxfCRjbrnrDJl2Lod3p7FtyQqqyw5yaHsSo2+5l7C4kVRXWNAbdOiNOnJSS/Hwc6JrP3+Hdd5u76T4EKIDqrXVsjN/J3sK91BQVUBJTQl6nZ5w93AuCr2IKI+os540F+/O4a5PNuHrasLf3UxybjlWu+LRYmd0YS5cf2cfvINcz/j8D2YsorrCSEh0NZP/PuGUzuUdwYJ3XmXP6rNM+HYaznp3dJqOSmvpKX0TWpWm1ffr0HQal06/n/hLxzsunjZIKcXyj95j66Jf6X3xWMJ798U7MBifsHBMTs6ODq/dk+JDCHFa2w4X82ViOpqmUVxZy87MUkam2wix1g1L7TkihB4JwQRGetSvPmq1WNnw00a2Lq4G4IH/XuLIFFqU3W6j5ujIvWMadNQ84aH1SCVlP6RhK6jrPKk563EbH45TvG/DDpEnfHNqp89Tj9M4dmvjhGcd+0Y7oQ1Nk7/Qz4O1tpa0bVuwWa0c3rWd1K2bKM3Lrd8/YOKVXHzb3Q6MsP1r1aG2Qoj2o2+4F33DvU7ZbrPY2b48g6TFh9i1+ghu3ma69vcnoIszSz7cA1rdqSJumOWU53YkOp0eZzf3Rh2bu+Qgmk6H78090Uw68j/YSdkPabj1DEDvcX5T4IuW9+tb/yY5cX3993qjEYPJjLW2rnjMPnjAUaF1SlJ8CCHQG3X0HxdB37HhZB8sJnlLHgc357J9WW194XHV38IIje3u4EjbDlOYG+Vrj1C69BCa8fjwTM1JTqttUXBMj/riw2h2wlJT3WC/zO3SuuS2ixDitJRdkZ9Rzvbl+0nZvJaKgmVMfeIFInrHOzq0NkHZFVXb86hOLgabwhjqhuvgQHRmKT7aqpLcHLb+/itZB/ai0+nxDY9gx7LfsVksXHzrXQyYNNnRIbZr0udDCNGs8tLT+OTRvzD65ukM+tMUR4cjRLMozsnmw7/ezYjrb2HI5GscHU67J30+hBDNavuS34C6++T7N6xFbzBQWVJCZWkJPUdejLuvn4MjFOL8HN61nV/fmo27rz99L5vo6HA6HSk+hBDn1GP4aFK2bGLZhycsEHl09qc1X3xMzJDhDLz8KkJ79HRckEKchbLbyUk9SG5aCgc3byBl80bCevbmTw8/htnlzEPMRcuQ2y5CiEZRSmG11GKtrcVutWJ2caU4J4sDG/7gwIa1FGQeZvRNdxAz7CLcvH1lGKhwuNqqSg7t2ErKlkRStiRSWVKMpunw7xLFgElX0nPkxfWrHIsLJ30+hBCtyma1sux//2X7krpprA0mM54BgXgFBePpH4ibrx8h3eMIiYmVk71ocTarheUfvcfO5YuxWa34hIbTbeAQuvYfTFB0dwymM8/kK5pOig8hhEOUFxaQnZJMSU4WxTnZlORkUZKbQ1lBPpaaakJ79OSap17EYOxY07KLtkEpxf71a9n4wzcUZBwi4dobiR02Aq+gYEeH1ilIh1MhhEO4+fgS7eN7yna73cb8Wc+TsXsnNotFig/R7GxWC4vfe4ddK5cS0Tuea59+SfogtWFSfAghWpxOp0cpRUSfvphdXBwdjuiAdiz9nV0rlzLxLzPoOfJiR4cjzkGKDyFEq6guL6M0P4+q8rJGT2EuRGMZzHVT2kf1G+jgSERjSM8vIUSrGDL5Guw2Kx/PuJ89a1dit9scHZLoQCJ6x2Mwmlj6wRz5t9UOSPEhhGgV3YeN4LZX3iUoujsL3prNRzMeICUp0dFhiQ7Cwy+ASQ8+wr51q1n07huODkecgxQfQohWsW/dmqOdAfvRf+IVFB3JYP7LL1BWkO/o0EQHETN0OMExsexevRybtWOvwNzeSZ8PIUSLO7J/L7+8MQuDyYyy27BZrQCEdI/DyV36f4jmc/Gtd/PVc4/x6WMPEzt8JD0uGo13UIijwxInkeJDCNHiKooKAbjjzbm4+/hhra2bKdXJzc3BkYmOJjgmlmnPv8ymX35g08/f88c384gZnMDwa/+MX0Sko8MTR8kkY0KIFldRXMTc+25l+LU3MmzqNEeHIzoJS20Ne1YvJ/Gn7yjNy2PApCvpNnAIwTGx6A0y10xzkxlOhRBtzvKP3mPLbz8RP3YCl06/D51O7+iQRCdhtVhY/90XJC38hdqqStz9/Lnu6Zdk5tNmJsWHEKLNUUqxY9kilrz/Lr1Gj+Wyux5Ap5cCRLQeu91GzsFkFrz9Cm4+vkx7bpajQ+pQZHp1IUSbo2ka8ZdOQG8wsui/b1JRVMDlDz8mM56KVqPT6bHb7Wg6HeVFBY4Op1OT4kMI0ap6jb4UV28ffn5tJl88/Qijb7qDyH4D0TTN0aGJdsJmtVBdXn70q4zqirLjj8vLqCorpbqiAmWzYbfbsVpq0el0oGmkbtmEm68vE+77m6PT6NTktosQwiHyDx/i97lvkXVgHwFR3Ui45s90GzhEipBOrKK4iOLsLIpzsijJzaY4J5vq8jKsNTVUVxwvNiw11ad9vtHshJObO07u7ji5uKIzGNB0OgxGE3a7DWtNDVH9B9F/whXoDfK3d3OTPh9CiHZBKcXhXdtZ/92XHN69g8i+A5j04CM4u8tnvzNQdjtZyfs5uHkDBzdtoCAjvX6fi6cXXoHBOHt4YjCZcHJzx9nNra64cHPHyc0NJ9fjj82ubrJasoNJ8SGEaFeUUqRs2cii/76Fm7cPN/xzNkazk6PDEufBWltLdsoBclMPUpCRTuGRDGwWC4FdYwjv1YcuffphdnEF6oqOvWtXsuarzyjNy8HZ3YOuAwYT2W8gvmEReAUEYXSS97+9keJDCNEu5aWnMe/JGcSNHMO4ux90dDiiEbIO7GPTrz+QsmUj1poa9EYjPsGh+ISGozMYyNq/l+KcLPRGI73HjMXJzZ3kxPUUZKQTPXgYA/80hZDuPWTodQcgo12EEO2Sf0QkF992F4vfe4deo8cSGhvn6JDEWST+/D2rPvsQ7+BQEq6+gci+A/AL73LKEOrSvFx2rljM1kW/gqbRpU8/xt55P2FxvR0UuXA0KT6EEG2Ks4cnAE6urg6ORJxNbloKqz77kIF/msLoG29H0515nVIP/wCGX3sjw6+9sRUjFG2ZrGorhGgzbFYLO5YsxD+yK75hEY4OR5zFxh+/xSswmJE33HLWwkOI05ErH0KIVlddXk7q1k0UZh6mqqyUmspKaioryNq/l+qKcsbf91dHhyjOoryokMO7thM7fKSskSKaRIoPIUSrqSwpZsey39ny209UlhTj5u2Ds6cXZhcXzC6u9B13ObEJI/DvEuXoUMUZlObl8u2LT6HT6xn0p6mODke0U1J8CCFaRXFONp89/jA2i4XY4aO4aNpNuPv6OToscR4KMtL59sWn0RuNTHvuZTz8/B0dkminpPgQQrSKlZ++j8Fs5o4338PlaKdS0X4UZWXy0Yz78Q2L4Jqn/oWbt4+jQxLtmPQSEkK0isLMDGrKyzmyf6+jQxFNkJ28H4BuA4dI4SEumEwyJoRoFaX5uSx5/11SkzYRM2Q4oT16YTAZcXJzJ7BrDF6BQY4OUZyFUorXrr8CgEun30/fyybKOjyiAZnhVAjRJiml2PfHKtZ8+QmVJSVYa2tRyo7eYGD6W+9LH5A2btXn/yPxp+8ACOwazaV33EdwTKyDoxJthRQfQoh2wWqx8P6D03FydeOmmW9gMJkcHVKT1VRWcnj3DjL27CTvUCpl+XkUZWXW7w+I7EZu2kEAelw0Gr/wLngFBeMVGIxXUHD9uidtnVKKtG1bWPvVZxRkpnPp7fcSmzBS1mIRMr26EKJ9KM4+QkVRIUMmX9MuC4/a6ip2rVzKrhVLyTuUgt1mw93Pn8CoaLoOGERRVggpWxKJ6j8IS/XxZeDzDqWStnUz1RXl9duc3T3wDgkjIDKKwKhogrrF4BMW3ubWPNE0jah+Awnr2ZuF77zGov++ydL//ZfuQy/iomk3ywgY0Shy5UMI4TBKKb6f9Ry5qQe54Z+vtJt+H6X5eWxd9Avbly6ktqqKbgOHEtm3P1369McrKLjR7VSVl1GSnUVxThbF2VkUZB4mN/UghVmZoBQGsxm/sAi8gkLwCgomqFt3InrHt6kVf4uzs9i3bjVJC3/Gyc2dG2e+jtFkdnRYwgHktosQot2oKC7iy2f+QU1lBVfO+L82vdhYVvI+Nv/6I/vXr8Hk5EyfS8fTf8Kf8PALaNbXqamsJDftINkHD1CYeZiirCMUZWVSWVKM0exE3Mgx9LlkPIFdo9tMp8/89DQ+/7+/Ezt8FBPu/6ujwxEOIMWHEKJdqSor5afXXuLIvr1MfeI5uvTp5+iQGrBZrSx893X2rl2JZ2AQAyZeSe8xYzE5u7RaDEopirKOsHftSnYsXUh5USG+YRFED06g26AhBHWNcfgaK+u++4I/vv6cwZOvYdSfb3NoLKL1SfEhhGh3bFYL3896niP793DxrXfT55JxbeKveqUUi+a8yZ41Kxh3z4PEjRzj8H4YdpuNQ9uT2LN2JalJm6guL8PF04ug6O64enmDUkf7nwQQEBmFf5eueAYEtvjP02a18uFf76E0L4f73vsMF0+vFn090bZIh1MhRLujNxi56pGnWP7xeyx+7232/bGKfuMup+vAwQ5bvKyypJiVn37A7tXLmfjA3+k56hKHxHEynV5PVP9BRPUfhN1mI3PfbtK2biYn9SB5h1KBuo6hKUmbqCotAcDk7IJPaBjeQSF4B4fiExpGaGxP3Hx8my2uvEOpVJYU02vMWCk8xFnJlQ8hRJuTnLieDT98TXbyfpzdPehzyTiGTb2+VYZz1lZVcuTAPnatWMKBDWsxmMxcfNvd9Bp9aYu/dnNTSlFRXEReWgq5h1IpOpJJUVYmRdlH6osS7+BQwnv1IXrQMLrE90enb9pVnfLCAubedyvOHp7c9c4HbapTrGgdcttFCNEh5KensWP5YrYvWYhnQCDXP/9vnNzcWuS1bFYLnz85g7y0FAC8goKJv3QCvS++DGf3jncuqiguImPPTg7v2kH6zq0UZR3BPyKSkX++jch+A8/rFo1Siu9nPkvati1Mffw5ovoPasHIRVslxYcQokPJTUvh08ceYuyd99P3skmnPaa2ugq7zQYKTM7O6PR6qivKKczMIKR7j7O2n5q0iWUfzaU4OwuA6555ibC43g7vwNlalFIc2b+XlZ99QNbRtXe6DRpKVL+BuHr54OrtXfd/L2/sdhvVZWXUVlVRUVxIaX4eBzasJWVLIvFjJ3DZXX9xcDbCUVqsz8ecOXOYM2cOaWlpAPTq1YtnnnmGiRMnkpaWRlRU1Gmf9/XXX3Pttdeez0sJIUS9LQt+Qqc3EBbX57T7d69axm//ea3BNoPJjLW2BoAR19/CkKuuPe1f8z++8i+SE9fjGxbBra/8B7/wLs2fQBunaRqhsXHc8MJs9q5ZwYJ3XuXgpg2kbElE2e3nfL53SBhXPvIkMYMTWiFa0RGcV/ERFhbGrFmziImJQSnFxx9/zOTJk0lKSqJHjx5kZWU1OP69995j9uzZTJw4sVmDFkJ0LvvWr8a/SyQ6/emvRFSWFNc/9goMJrBrNP5dotB0OgozD7Pmy08oPJLBoCum4h8RWX+spbqa5MT1ANz88lvoDZ27D76macSNvJi4kRcDYLfbqCotpaK4iIqiQiqKi9AbDDi5uWN0csLV2wc3H1+ZVEyctwu+7eLj48Ps2bOZPn36Kfv69+/PgAED+OCDDxrdntx2EUKcLGnhz6z96jNqKitw8/UjILIrgVHRhMTEEhQTi8nJmW2LF5CcuI7sgweorarC5OxMz1GXknDNDRzctIHV8z6iqqyUwK7R9BozlrgRY6goKuKjGfdx5Yz/I2bIcEenKUS71ip9Pmw2G9988w233norSUlJ9OzZs8H+zZs3M2jQINauXcvw4Y3/UEvxIYQ4HUttDalJm8g+eIDc1IPkpCRTXV4GmkZU3wH0G/8nIvsNQEOjIPMwe9euZMP8r+lzyTjG3fMQNquFlKRN7FqxlNSkRIxOTtzwz1f49a3ZVJeXMeG+vxHeq0+bmFtEiPaoRYuPHTt2kJCQQHV1NW5ubsybN49Jk07tAHb//fezYsUKdu/efdb2ampqqKmpaRB8eHi4FB9CiLM6NuNnxu4dbF+6kJyUZDwDAulx0Wg8/ANI27aFAxv+YPKjTxM9aGiD55YXFjDvqUeI6jeQoVOv45c3XibrwD78IiLpMXwU3RNG4B0U4qDMhGifWrT4qK2tJT09nZKSEr799lvef/99Vq5c2eDKR1VVFcHBwTz99NPMmDHjrO0999xzPP/886dsl+JDCNFYSimyk/ezddEvHNqxlYriIrxDwhh61bVnnJ9jyfvvsu+PVYy6+Q7cffyO3rZZX78/4ZobGH7tja2VghDtXqsOtR07dizdunVj7ty59ds+/fRTpk+fTmZmJv7+Z19eWa58CCGam81qOeesqBXFRfz2n9c4tD0JqJs11CsoBDdvb6orKhh394MEdo1ujXCF6BBadXp1u93eoHgA+OCDD7jyyivPWXgAmM1mzGbpKS2EaD6NmY7d1cuba578JzWVFVSVluLu5+ewadyF6GzOq/h44oknmDhxIhEREZSVlTFv3jxWrFjBokWL6o9JTk5m1apVLFiwoNmDFUKI5mZ2ccXs4uroMIToVM6r+MjNzeWWW24hKysLT09P4uPjWbRoEZdddln9MR9++CFhYWGMGzeu2YMVQgghRPsn06sLIYQQ4oKdz+/vzrFwgRBCCCHaDCk+hBBCCNGqpPgQQgghRKuS4kMIIYQQrUqKDyGEEEK0Kik+hBBCCNGqpPgQQgghRKuS4kMIIYQQrUqKDyGEEEK0Kik+hBBCCNGqpPgQQgghRKs6r4XlWsOxpWZKS0sdHIkQQgghGuvY7+3GLBnX5oqPsrIyAMLDwx0ciRBCCCHOV1lZGZ6enmc9ps2tamu32zly5Aju7u5omtbs7ZeWlhIeHs7hw4c75Kq5HT0/6Pg5Sn7tm+TXvkl+TaeUoqysjJCQEHS6s/fqaHNXPnQ6HWFhYS3+Oh4eHh3yH9YxHT0/6Pg5Sn7tm+TXvkl+TXOuKx7HSIdTIYQQQrQqKT6EEEII0ao6XfFhNpt59tlnMZvNjg6lRXT0/KDj5yj5tW+SX/sm+bWONtfhVAghhBAdW6e78iGEEEIIx5LiQwghhBCtSooPIYQQQrQqKT6EEEII0ao6ZPGxZcsWLrvsMry8vPD19eXuu++mvLy8wTEPPfQQAwcOxGw2069fv0a1O2bMGDRNa/B17733tkAGZ9dS+VVXV/PAAw/g6+uLm5sbV199NTk5OS2Qwdk1Jr/09HQuv/xyXFxcCAgI4NFHH8VqtZ613cjIyFPev1mzZrVkKqfVUvkVFhZy44034uHhgZeXF9OnTz+l3dawf/9+Jk+ejJ+fHx4eHowYMYLly5c3OGbp0qUMHz4cd3d3goKCeOyxx86ZX1v5/LVUfm3l89eY/BITE7n00kvx8vLC29ub8ePHs23btrO2257ev6bk11bePzh3jh999NEp78Wxr9zc3DO226znUNXBZGZmKm9vb3XvvfeqvXv3qo0bN6rhw4erq6++usFxDz74oHrnnXfUzTffrPr27duotkePHq3uuusulZWVVf9VUlLSAlmcWUvmd++996rw8HC1dOlStWnTJjVs2DA1fPjwFsjizBqTn9VqVb1791Zjx45VSUlJasGCBcrPz0898cQTZ227S5cu6oUXXmjw/pWXl7d0Sg20ZH4TJkxQffv2VevXr1erV69W0dHR6oYbbmjplE4RExOjJk2apLZt26b279+v7r//fuXi4qKysrKUUkpt3bpVmUwm9fzzz6sDBw6oFStWqB49eqgZM2actd228PlTquXyawufP6XOnV9ZWZny8fFRt912m9q7d6/auXOnuvrqq1VgYKCqra09Y7vt5f1ran5t5f1T6tw5VlZWNngfsrKy1Pjx49Xo0aPP2m5znkM7XPExd+5cFRAQoGw2W/227du3K0AdOHDglOOfffbZ8yo+Hn744WaKtGlaKr/i4mJlNBrVN998U79tz549ClDr1q1rltgbozH5LViwQOl0OpWdnV1/zJw5c5SHh4eqqak5Y9tdunRRr7/+eovF3hgtld/u3bsVoBITE+u3/fbbb0rTNJWZmdlC2ZwqLy9PAWrVqlX120pLSxWgFi9erJRS6oknnlCDBg1q8LyffvpJOTk5qdLS0jO23RY+fy2VX1v5/DUmv8TERAWo9PT0+mPOdg46pr28f03Jr628f0o1LseT5ebmKqPRqD755JOztt2c59AOd9ulpqYGk8nUYFEbZ2dnANasWXPB7X/++ef4+fnRu3dvnnjiCSorKy+4zfPRUvlt3rwZi8XC2LFj67f16NGDiIgI1q1b1/SAz1Nj8lu3bh19+vQhMDCw/pjx48dTWlrKrl27ztr+rFmz8PX1pX///syePfucl8KbW0vlt27dOry8vBg0aFD9trFjx6LT6diwYUNLpHJavr6+xMbG8sknn1BRUYHVamXu3LkEBAQwcOBAoO5n4OTk1OB5zs7OVFdXs3nz5rO27+jPX0vl11Y+f43JLzY2Fl9fXz744ANqa2upqqrigw8+IC4ujsjIyLO23x7ev6bk11beP2hcjif75JNPcHFx4Zprrjln+812Dm2WEqYN2blzpzIYDOrf//63qqmpUYWFherqq69WgHrppZdOOf58rnzMnTtXLVy4UG3fvl199tlnKjQ0VE2ZMqWZMzi7lsrv888/VyaT6ZTtgwcPVv/4xz+aI/RGaUx+d911lxo3blyD51VUVChALViw4Ixtv/rqq2r58uVq27Ztas6cOcrLy0v97W9/a9F8TtZS+b344ouqe/fup2z39/dX7777bvMnchaHDx9WAwcOVJqmKb1er4KDg9WWLVvq9y9atEjpdDo1b948ZbVaVUZGhho5cqQC1Lx5887Yblv4/CnVMvm1lc+fUufOTymlduzYobp166Z0Op3S6XQqNjZWpaWlnbXd9vL+KXX++bWl90+pxuV4ori4OHXfffeds93mPIe2mysfjz/++Bk7yBz72rt3L7169eLjjz/m1VdfxcXFhaCgIKKioggMDDznEr/ncvfddzN+/Hj69OnDjTfeyCeffML8+fM5ePBgh8ivJbWF/P7+978zZswY4uPjuffee3n11Vd5++23qamp6RD5taTG5qeU4oEHHiAgIIDVq1ezceNGrrrqKq644gqysrIAGDduHLNnz+bee+/FbDbTvXt3Jk2aBHDWn0Fb+Py1ZH4tqTnzq6qqYvr06Vx00UWsX7+etWvX0rt3by6//HKqqqrOGEN7ef+aml9La84cT7Ru3Tr27NnD9OnTzxlDs55Dm1SyOEBubq7as2fPWb9Ovh+enZ2tysrKVHl5udLpdOrrr78+pd3zufJxsvLycgWohQsXNun5J3J0fkuXLlWAKioqarA9IiJCvfbaaxeSmlKqefN7+umnT8kpJSVFAWet7k+2c+dOBai9e/e2+/w++OAD5eXl1WCbxWJRer1eff/9962W35IlS5ROpzulI2F0dLSaOXNmg212u11lZmaqysrK+j4rGzdubHRMjvj8tVR+beXz15j83n///VP6LdXU1CgXFxf1xRdfNDqmtvr+NSW/ln7/mjvHE91xxx2qX79+TYrpQs6hhvMvVxzD398ff3//83rOsXvmH374IU5OTlx22WXNGtPWrVsBCA4OvuC2HJ3fwIEDMRqNLF26lKuvvhqAffv2kZ6eTkJCQpPbPaY580tISODFF18kNzeXgIAAABYvXoyHhwc9e/ZsdPtbt25Fp9PVt3EhHJ1fQkICxcXFbN68uf6+7rJly7Db7QwdOrSpadVrbH7H7uGf/Be+TqfDbrc32KZpGiEhIQB88cUXhIeHM2DAgEbH5IjPX0vl11Y+f43Jr7KyEp1Oh6ZpDfZrmnbKz+Bs2ur715T8Wvr9g5b5N1peXs7XX3/NzJkzmxTTBZ1Dm1TutHFvv/222rx5s9q3b5965513lLOzs3rzzTcbHHPgwAGVlJSk7rnnHtW9e3eVlJSkkpKS6v86zcjIULGxsWrDhg1KKaWSk5PVCy+8oDZt2qRSU1PVjz/+qLp27apGjRrVIfJTqm6oWEREhFq2bJnatGmTSkhIUAkJCa2am1Lnzu/YUNRx48aprVu3qoULFyp/f/8GQ1E3bNigYmNjVUZGhlJKqT/++EO9/vrrauvWrergwYPqs88+U/7+/uqWW27pEPkpVTfUtn///mrDhg1qzZo1KiYmptWH2ubl5SlfX181depUtXXrVrVv3z71yCOPKKPRqLZu3Vp/3L///W+1fft2tXPnTvXCCy8oo9Go5s+fX7+/rX7+Wio/pdrG568x+e3Zs0eZzWZ13333qd27d6udO3eqm266SXl6eqojR46cNr/29P41JT+l2sb719gcj3n//feVk5PTKVdslGr5c2iHLD5uvvlm5ePjo0wmk4qPjz/t8KHRo0cr4JSv1NRUpZRSqampClDLly9XSimVnp6uRo0apXx8fJTZbFbR0dHq0Ucfdcg49ZbITymlqqqq1P3336+8vb2Vi4uLmjJlSv248NbUmPzS0tLUxIkTlbOzs/Lz81MzZsxQFoulfv/y5csb5Lt582Y1dOhQ5enpqZycnFRcXJx66aWXVHV1dWulVa8l8lNKqYKCAnXDDTcoNzc35eHhoW6//XZVVlbWGik1kJiYqMaNG6d8fHyUu7u7GjZs2CkdZS+++OL692Lo0KGn7G/Ln7+WyE+ptvP5a0x+v//+u7rooouUp6en8vb2VpdcckmDIaXt/f073/yUajvvn1KNy1EppRISEtSf//zn07bR0udQTSmlmnS9RQghhBCiCdpu93ohhBBCdEhSfAghhBCiVUnxIYQQQohWJcWHEEIIIVqVFB9CCCGEaFVSfAghhBCiVUnxIYQQQohWJcWHEEIIIVqVFB9CCCGEaFVSfAghhBCiVUnxIYQQQohWJcWHEEIIIVrV/wedRsSSWc51YwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"here are the HD centers for\",len(cantFill),\"cantFill HDs with border or big enclaves\")\n",
    "for u in borderUnits:\n",
    "    plotPoly(unitGeom[u])\n",
    "for t in cantFill:\n",
    "    plotPoly(hdCP[t].buffer(0.02))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "5269a224-4a97-417c-99af-6a98df0087ae",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the barredJettisonSet (cannot be shed in below MUSTFREE code) is {9675, 9676, 9677}\n",
      "working on avg unit-to-HDcp dist for HD 0\n",
      "working on avg unit-to-HDcp dist for HD 800\n",
      "working on avg unit-to-HDcp dist for HD 1600\n",
      "working on avg unit-to-HDcp dist for HD 2400\n",
      "working on avg unit-to-HDcp dist for HD 3200\n",
      "working on avg unit-to-HDcp dist for HD 4000\n",
      "working on avg unit-to-HDcp dist for HD 4800\n",
      "working on avg unit-to-HDcp dist for HD 5602\n",
      "working on avg unit-to-HDcp dist for HD 6402\n",
      "working on avg unit-to-HDcp dist for HD 7202\n",
      "working on avg unit-to-HDcp dist for HD 8002\n",
      "working on avg unit-to-HDcp dist for HD 8802\n",
      "working on avg unit-to-HDcp dist for HD 9602\n",
      "all unit-toHDcp distances computed\n"
     ]
    }
   ],
   "source": [
    "barredJettisonSet = set(list())\n",
    "for u in range(nUnits):\n",
    "    if allUnits[u]% 1 > 0.23 and allUnits[u]%1 < 0.27:\n",
    "        barredJettisonSet.add(u)\n",
    "print(\"the barredJettisonSet (cannot be shed in below MUSTFREE code) is\",barredJettisonSet)\n",
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%800 == 0:\n",
    "        print(\"working on avg unit-to-HDcp dist for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "print(\"all unit-toHDcp distances computed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "6e2e44bd-a084-42f6-b533-5dc6d21912a9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this code will solve large enclaves so HD and complement are contiguous for 112 HDs\n",
      "working on HD 114 cantFill 0 of 112 .Time is now 0\n",
      "working on HD 2048 cantFill 20 of 112 .Time is now 0\n",
      "working on HD 3537 cantFill 40 of 112 .Time is now 2\n",
      "working on HD 10018 cantFill 60 of 112 .Time is now 2\n",
      "working on HD 3067 cantFill 80 of 112 .Time is now 7\n",
      "working on HD 8786 cantFill 100 of 112 .Time is now 7\n",
      "after the MustFree code run, we have the following for cluster usage\n",
      "current avg use and its sd are 1.00593 0.10366\n",
      "CCB cluster 0 = unit 9675 with pop 211407.0 now has use of 1.0055979672364956\n",
      "CCB cluster 1 = unit 9676 with pop 82367.0 now has use of 1.0302650347613453\n",
      "CCB cluster 2 = unit 9677 with pop 83357.0 now has use of 1.0851585809742463\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#THIS IS THE MUSTFREE CODE - for high-pop HDs with map-border enclaves, can't fill; \n",
    "#  must jettison some inHD map-boundary units to connect the enclave to the larger complement\n",
    "#For each HD to be triaged, define the list(s) of contiguous enclave units that are on the map boundary, \n",
    "#  and the in-HD map-boundary segments.  ID which in-HD MBS's adjoin one vs. two enclaves.\n",
    "#     Fill all internal enclaves, and all boundary enclaves < 0.05 aDP.\n",
    "#   Then each loop, look for boundary enclaves that can be filled without overpopping.\n",
    "#     If none, pick the 1/2 has-1-boundary-enclave-neighbor that is least painful to jettison to free an enclave.\n",
    "#       (Jettison score based on pop-to-Free and distance from HDcP)\n",
    "#         Update HDpop, HDlist, and enclave & HD-boundary associations, then re-loop\n",
    "# Later, we will swell-fill to square up pop (w/ checkEnclave) biasing toward close-to-hdCP, underused\n",
    "borderSet = set(borderUnits)\n",
    "debug, debugPlot = False, False\n",
    "startTime = time.time()  #takes about 1.5sec per HD triage\n",
    "clusterJettisonBoost = 3.  #this discourages jettisoning of underused clusters\n",
    "print(\"this code will solve large enclaves so HD and complement are contiguous for\",len(cantFill),\"HDs\")\n",
    "nEnclavesPerHD = [0 for t in range(nHDs)]\n",
    "HDenclaveLists = [list() for t in range(nHDs)]\n",
    "for iii,t in enumerate(cantFill):\n",
    "    if iii %20 == 0:\n",
    "        print(\"working on HD\",t,\"cantFill\",iii,\"of\",len(cantFill),\".Time is now\",int(time.time() - startTime) )\n",
    "    shedUs = list()    \n",
    "    enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "    nEnclavesPerHD[t] = len(enclaveLists)\n",
    "    HDenclaveLists[t] = enclaveLists.copy()\n",
    "    if debug:\n",
    "        print(\"pre-adjust HDpop for HD\",t,\"is\",HDvPop[t],\"I found\",len(enclaveLists),\"TOTAL enclaves\")\n",
    "    internalEnclaves, edgeEnclaves, combinedEnclBorderList = list(), list(), list()\n",
    "    for jjj, eL in enumerate(enclaveLists.copy() ):\n",
    "        enclaveBorderList = list ( set(eL).intersection(borderSet) )\n",
    "        if debug:\n",
    "            print(\"In enclave\",jjj,\"I found\",len(enclaveBorderList),\"units that were enclaved and are in the map borderSet\")\n",
    "        combinedEnclBorderList += enclaveBorderList\n",
    "        ePop = np.sum( [unitPop[u] for u in eL] )\n",
    "        if len(enclaveBorderList) == 0 or ePop < 0.05 * aDP:  #internal or small enclave.  Fill it\n",
    "            if ePop > 0:  #in a prev treatment, could be an empty (surrounded) unit that we don't care about\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += ePop\n",
    "            internalEnclaves.append(eL)\n",
    "        else:\n",
    "            edgeEnclaves.append(eL)\n",
    "    if debug:\n",
    "        print(\"Of these\",len(internalEnclaves),\"were internal or small, so I filled them, leaving\",\n",
    "              len(edgeEnclaves),\"non-small border = edge enclaves\" )\n",
    "    if debugPlot:\n",
    "        print(\"Here is the original HD, internal enclaves ('x') and non-small border enclaves by enclave no\")\n",
    "        plotPoly(hdCP[t].buffer(0.3))\n",
    "        for u in HDunitList[t]:\n",
    "            if unitPop[u] > 0:\n",
    "                plotPoly(unitGeom[u],0.2)\n",
    "        for L in internalEnclaves:\n",
    "            for u in L:\n",
    "                if unitPop[u] > 0:\n",
    "                    plotPoly(unitGeom[u],1.5)\n",
    "                    plotCenter(\"x\",unitCP[u],8)\n",
    "        for L in edgeEnclaves: #############\n",
    "            for u in L:\n",
    "                if unitPop[u] > 0:\n",
    "                    plotPoly(unitGeom[u])\n",
    "                    #plotCenter(\"e\",unitCP[u],8)\n",
    "        #plotPoly(MAP,0.4)\n",
    "        #plt.show()\n",
    "    enclaveLists, combinedEnclBorderSet = list(), set(combinedEnclBorderList)\n",
    "    if len(edgeEnclaves) > 0:\n",
    "        # Now, we order by chain connectivity of HD and enclave sublists to be H0-E0-H1-E1 ... En-Hn+1\n",
    "        nonHDborderSet = borderSet.difference(  set(HDunitList[t]) )\n",
    "        nonHDlongBorderSet = nonHDborderSet.difference(combinedEnclBorderSet) #long=non HD boundary excluding enclaves\n",
    "        remainingEnclBorderSet = combinedEnclBorderSet.copy()\n",
    "        remainingHDborderSet =   borderSet.intersection(set(HDunitList[t]) )\n",
    "        #Now find the \"HDender\" unit which borders the non-enclave nonHD boundary, then find opp end of this HD bdry piece\n",
    "        HDender = list(set(getAdjoiners(nonHDlongBorderSet,unitNbrs)).intersection(remainingHDborderSet) )[0]\n",
    "        firstHDborderSet = getContigFromStarter(HDender,remainingHDborderSet,unitNbrs)\n",
    "        HDstarter = list(set(getAdjoiners(remainingEnclBorderSet,unitNbrs)).intersection(firstHDborderSet))[0]\n",
    "        HDborderSublists = [ list(firstHDborderSet) ]\n",
    "        unused = [1 for eL in edgeEnclaves]\n",
    "        eLadjoiners = [getAdjoiners(eL,unitNbrs) for eL in edgeEnclaves ]\n",
    "        for j in range(len(edgeEnclaves)): #find the enclave with the most HDstarter neighbors (at least 1)\n",
    "            found = False\n",
    "            for i,eL in enumerate(edgeEnclaves):\n",
    "                if unused[i] == 1:\n",
    "                    HDadjSet = set(HDborderSublists[j]).intersection(set(eLadjoiners[i]))\n",
    "                    if len(HDadjSet) > 0:\n",
    "                        unused[i] = 0\n",
    "                        eNo = i\n",
    "                        found = True\n",
    "                        remainingEnclBorderSet = remainingEnclBorderSet.difference(set(edgeEnclaves[eNo]) )\n",
    "                        enclaveLists.append(edgeEnclaves[eNo])\n",
    "                        remainingHDborderSet = remainingHDborderSet.difference(set(HDborderSublists[j]) )\n",
    "                        HDstarter = list(set(eLadjoiners[i]).intersection(remainingHDborderSet))[0]       \n",
    "                        HDborderSublists.append(getContigFromStarter(HDstarter,remainingHDborderSet,unitNbrs) )\n",
    "                        break\n",
    "                if found:\n",
    "                    break\n",
    "\n",
    "        enclavePops = [np.sum([unitPop[u] for u in L]) for L in enclaveLists]\n",
    "        #print(\"prior to adjustments, border enclavePops are\",enclavePops)         \n",
    "\n",
    "        nHDBS, nEnclaves = len(HDborderSublists), len(enclaveLists)\n",
    "        popToFree, freeingCounties, freeingUnits = [0. for n in range(nHDBS)], [list() for n in range(nHDBS) \n",
    "                                                                               ],[list() for n in range(nHDBS)]\n",
    "        for j,L in enumerate(HDborderSublists):\n",
    "            for u in L:\n",
    "                if int(allUnits[u]) == allUnits[u]:  #this border unit is a vtd\n",
    "                    c = countyNo[parentVTDno[allUnits[u]]]   #countyNo[allUnits[u]]\n",
    "                    if c not in freeingCounties[j]:\n",
    "                        if countyPop[c] < 0.1 * aDP:  #plan to add all in-county pop\n",
    "                            freeingCounties[j].append(c)\n",
    "                        else:\n",
    "                            popToFree[j] += unitPop[u]\n",
    "                            freeingUnits[j].append(u)\n",
    "                else: #border unit is a full county or cluster, or in a dense county.  Add the whole unit pop\n",
    "                    popToFree[j] += unitPop[u]\n",
    "                    freeingUnits[j].append(u)\n",
    "            for c in freeingCounties[j]:  #include ALL in-HD pop from each non-unit border county, not just its border units\n",
    "                #plotPoly(countyGeom[c],0.1)\n",
    "                for u in countyUnitList[c]:\n",
    "                    if u in HDunitList[t]:\n",
    "                        popToFree[j] += unitPop[u]\n",
    "                        freeingUnits[j].append(u)\n",
    "        freeingCP = [ getHDcp(  unitCP, unitPop, L) for L in freeingUnits ]\n",
    "        freeingScore = [ pTF/aDP - 0.5*freeingCP[j].distance(hdCP[t]) / avgDist[t] for j,pTF in enumerate(popToFree) ]\n",
    "        for j, fU in enumerate(freeingUnits):  #in above 0.5 is a fudgy\n",
    "            if len(barredJettisonSet.intersection(set(fU)) ) > 0: #has a cluster we want to hold onto\n",
    "                freeingScore[j] += clusterJettisonBoost #  ..so increase its score (make it harder to drop)\n",
    "        if debugPlot:\n",
    "            print(\"plotting the freeing units with negative numbers for each freeing group\")\n",
    "            for j,L in enumerate(freeingUnits):\n",
    "                for u in L:\n",
    "                    if unitPop[u] > 0:\n",
    "                        #plotPoly(unitGeom[u],0.5)\n",
    "                        plotCenter(\"-\"+str(j),unitGeom[u],6)\n",
    "                        pass\n",
    "            print(\"plotting the enclaveLists, with + numbers for each enclave\")\n",
    "            for j,L in enumerate(enclaveLists):\n",
    "                for u in L:\n",
    "                    if unitPop[u] > 0:\n",
    "                        plotPoly(unitGeom[u])\n",
    "                        plotCenter(j,unitCP[u],8)\n",
    "                        pass\n",
    "    \n",
    "    while len(enclaveLists) > 0:\n",
    "        if HDvPop[t] + np.min(enclavePops) < 1.05*aDP or np.min(enclavePops) < 0.05 * aDP:  #fill the smallest enclave\n",
    "            eNo = enclavePops.index(np.min(enclavePops))\n",
    "            HDunitList[t] += enclaveLists[eNo]\n",
    "            HDvPop[t] += enclavePops[eNo]\n",
    "            #print(t,\"=t. Absorbing enclave\",eNo,\"with pop\",enclavePops[eNo],\"HD total pop now\",int(HDfreePop[t]) )\n",
    "            enclaveBUs = list(set(enclaveLists[eNo]).intersection(set(borderUnits)) )\n",
    "            enclaveBpop = np.sum([unitPop[u] for u in enclaveBUs])\n",
    "            sNo, dropped_sNo = eNo, eNo+1\n",
    "            freeingScore[sNo] += freeingScore[sNo+1]+enclaveBpop/aDP\n",
    "            freeingUnits[sNo] += freeingUnits[sNo+1]+enclaveBUs\n",
    "            popToFree[sNo]    +=    popToFree[sNo+1]+enclaveBpop\n",
    "        else: #jettison one of the two end HD border lists; pick the less painful path to freedom\n",
    "            distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "            starterU = HDunitList[t][distList.index(np.min(distList))]\n",
    "            eNo, dropped_sNo = 0,0\n",
    "            if starterU not in freeingUnits[-1]:  #we can't drop the home unit, even to save an underused corner\n",
    "                if freeingScore[-1] < freeingScore[0] or starterU in freeingUnits[0]:\n",
    "                    eNo, dropped_sNo = len(enclaveLists)-1,len(enclaveLists)\n",
    "            barredIncluded0 = barredJettisonSet.intersection(set(freeingUnits[0]))\n",
    "            barredIncluded_1 = barredJettisonSet.intersection(set(freeingUnits[-1]))\n",
    "            #if len(barredIncluded0.union(barredIncluded_1)) > 0:\n",
    "            #    print(\"We are considering dropping an end unit to free from t\",t,\". Chosen, beg, end, scores are\")\n",
    "            #    print(dropped_sNo,barredIncluded0, barredIncluded_1, freeingScore[0], freeingScore[-1])\n",
    "            HDunitList[t] = list( set(HDunitList[t]).difference(set(freeingUnits[dropped_sNo]) ) )\n",
    "            HDvPop[t] -= popToFree[dropped_sNo]\n",
    "            #print(t,\"= t. Jettisoning HDborder\",dropped_sNo,\"with popToFree\",popToFree[dropped_sNo] )\n",
    "        del enclaveLists[eNo]\n",
    "        del enclavePops[eNo]\n",
    "        if debug:\n",
    "            print(t,\"= t. Now we have\",len(enclaveLists),\"left trapped.  Picked eNo, freeScores were\", eNo,freeingScore)\n",
    "        del freeingScore[dropped_sNo]\n",
    "        del freeingUnits[dropped_sNo]\n",
    "        del popToFree   [dropped_sNo] \n",
    "\n",
    "    #plotPoly(MAP,0.4)\n",
    "    if debugPlot:\n",
    "        plt.show()    \n",
    "        \n",
    "unitUse = [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t]*nDistricts\n",
    "print(\"after the MustFree code run, we have the following for cluster usage\")\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"= unit\",u,\"with pop\",unitPop[u],\"now has use of\",unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "66e91b98-63a9-47db-af63-039ac47b1835",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "ca9ce3cb-c150-4f39-ae55-f781d39d7f57",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "postMustFreeUnitList = [HDunitList[t].copy() for t in range(nHDs)] #safekeeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "c32dd108-073b-48aa-99ce-fea50c8d023c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([HDvPop[t] for t in popHDlist] )\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "f58fe2d0-3c62-412f-8984-ff5d67ea9b10",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "After above work, re-classification of contiguity problems?\n",
      "working on HD 0\n",
      "working on HD 500\n",
      "working on HD 1000\n",
      "working on HD 1500\n",
      "working on HD 2000\n",
      "working on HD 2500\n",
      "working on HD 3000\n",
      "working on HD 3500\n",
      "working on HD 4000\n",
      "working on HD 4500\n",
      "working on HD 5000\n",
      "working on HD 5500\n",
      "working on HD 6000\n",
      "working on HD 6500\n",
      "working on HD 7000\n",
      "working on HD 7500\n",
      "working on HD 8000\n",
      "working on HD 8500\n",
      "working on HD 9000\n",
      "working on HD 9500\n",
      "working on HD 10000\n",
      "out of 10082 total HDs, there were 9807 103 0 172 HDs that were clean, discontig only, enclave-only, both problems after triage\n"
     ]
    }
   ],
   "source": [
    "#THIS is the FINDSTILLBROKEN code\n",
    "print(\"After above work, re-classification of contiguity problems?\")\n",
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()\n",
    "for t in popHDlist:\n",
    "    if t%500 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems after triage\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "1ef683a2-4429-4a91-b1ea-a9b0950dea22",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on current HD diam for HD number 0\n",
      "working on current HD diam for HD number 1000\n",
      "working on current HD diam for HD number 2000\n",
      "working on current HD diam for HD number 3000\n",
      "working on current HD diam for HD number 4000\n",
      "working on current HD diam for HD number 5002\n",
      "working on current HD diam for HD number 6002\n",
      "working on current HD diam for HD number 7002\n",
      "working on current HD diam for HD number 8002\n",
      "working on current HD diam for HD number 9002\n",
      "working on current HD diam for HD number 10002\n",
      "here is the histogram of HD diameter = sqrt(area)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "HDdiam = [0. for t in range(nHDs)]\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%1000 == 0:\n",
    "        print(\"working on current HD diam for HD number\",t)\n",
    "    HDdiam[t] = (HDpoly[t].intersection(MAP) ).area ** 0.5\n",
    "plt.hist([HDdiam[t] for t in popHDlist])\n",
    "print(\"here is the histogram of HD diameter = sqrt(area)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "45e3c17c-8c16-4bc5-b7fc-25b9250ed11a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here, we will regrow all disco'd HDs off by more than 37683 but less than 188419\n",
      "... from the contiguous block that contains the hdCP (not full regrowth).  We will swell out, avoiding enclaves\n",
      "This is a total of 275 HDs to triage in this block\n",
      "working on swell-filling discontig HD 300 our 1 th HD we think we can swell out of 275 0.001 sec elapsed\n",
      "working on swell-filling discontig HD 729 our 11 th HD we think we can swell out of 275 240.642 sec elapsed\n",
      "working on swell-filling discontig HD 1867 our 21 th HD we think we can swell out of 275 255.9 sec elapsed\n",
      "working on swell-filling discontig HD 3909 our 31 th HD we think we can swell out of 275 506.43 sec elapsed\n",
      "working on swell-filling discontig HD 4456 our 41 th HD we think we can swell out of 275 947.662 sec elapsed\n",
      "working on swell-filling discontig HD 5018 our 51 th HD we think we can swell out of 275 1376.533 sec elapsed\n",
      "working on swell-filling discontig HD 6120 our 61 th HD we think we can swell out of 275 1493.458 sec elapsed\n",
      "working on swell-filling discontig HD 6937 our 71 th HD we think we can swell out of 275 1857.25 sec elapsed\n",
      "working on swell-filling discontig HD 7690 our 81 th HD we think we can swell out of 275 2256.532 sec elapsed\n",
      "working on swell-filling discontig HD 9546 our 91 th HD we think we can swell out of 275 2462.931 sec elapsed\n",
      "working on swell-filling discontig HD 10052 our 101 th HD we think we can swell out of 275 2467.76 sec elapsed\n",
      "working on swell-filling discontig HD 215 our 111 th HD we think we can swell out of 275 2583.573 sec elapsed\n",
      "working on swell-filling discontig HD 742 our 121 th HD we think we can swell out of 275 2738.956 sec elapsed\n",
      "working on swell-filling discontig HD 1504 our 131 th HD we think we can swell out of 275 2818.223 sec elapsed\n",
      "working on swell-filling discontig HD 2056 our 141 th HD we think we can swell out of 275 2914.257 sec elapsed\n",
      "working on swell-filling discontig HD 2863 our 151 th HD we think we can swell out of 275 2951.977 sec elapsed\n",
      "working on swell-filling discontig HD 3036 our 161 th HD we think we can swell out of 275 3029.096 sec elapsed\n",
      "working on swell-filling discontig HD 4197 our 171 th HD we think we can swell out of 275 3470.157 sec elapsed\n",
      "working on swell-filling discontig HD 4848 our 181 th HD we think we can swell out of 275 3636.106 sec elapsed\n",
      "working on swell-filling discontig HD 5284 our 191 th HD we think we can swell out of 275 3921.213 sec elapsed\n",
      "working on swell-filling discontig HD 5719 our 201 th HD we think we can swell out of 275 4670.19 sec elapsed\n",
      "working on swell-filling discontig HD 6468 our 211 th HD we think we can swell out of 275 5174.164 sec elapsed\n",
      "working on swell-filling discontig HD 7348 our 221 th HD we think we can swell out of 275 6195.37 sec elapsed\n",
      "working on swell-filling discontig HD 8770 our 231 th HD we think we can swell out of 275 6409.315 sec elapsed\n",
      "working on swell-filling discontig HD 9388 our 241 th HD we think we can swell out of 275 6810.014 sec elapsed\n",
      "working on swell-filling discontig HD 9604 our 251 th HD we think we can swell out of 275 7120.991 sec elapsed\n",
      "working on swell-filling discontig HD 9968 our 261 th HD we think we can swell out of 275 7257.802 sec elapsed\n",
      "working on swell-filling discontig HD 10038 our 271 th HD we think we can swell out of 275 7470.8 sec elapsed\n",
      "we partially regrew 183 HDs, leaving 92 to regrow from scratch\n"
     ]
    }
   ],
   "source": [
    "### THIS IS THE CANSWELL CODE  #Note -- this has not yet implemented the \"avoidedEnclave\" shortcut\n",
    "print(\"Here, we will regrow all disco'd HDs off by more than\",int(aDP-minPostFixPop),\"but less than\",int(0.25*aDP) )\n",
    "print(\"... from the contiguous block that contains the hdCP (not full regrowth).  We will swell out, avoiding enclaves\")\n",
    "HDnAddedUnits = [0 for t in range(nHDs)]\n",
    "maxGap = 0.9 * np.median(unitPop)  #set a reasonable gap prior to picking the last block\n",
    "HDdiam = [HDpoly[t].area ** 0.5 for t in range(nHDs) ] #in case not defined before\n",
    "badDiscoList = list()\n",
    "nCanSwell = 0\n",
    "triageList = discontigOnly + bothProblems\n",
    "print(\"This is a total of\",len(triageList),\"HDs to triage in this block, including some too discontig to fix here\")\n",
    "startTime = time.time()\n",
    " \n",
    "for i,t in enumerate(triageList): #canSwell\n",
    "    if i%10 == 0:\n",
    "        SEC = r3(time.time()-startTime)\n",
    "        print(\"working on swell-filling discontig HD\",t,\"our\",i+1,\"th HD we can possibly swell out of\",len(triageList),SEC,\"sec elapsed\" )\n",
    "    distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "    starterU = HDunitList[t][distList.index(np.min(distList))]  #starter = unit with centroid closest to the hd center\n",
    "    contigUs = getContigFromStarter(starterU, HDunitList[t], unitNbrs)\n",
    "    contigPop = np.sum( [ unitPop[u] for u in contigUs ] )\n",
    "    if contigPop < 0.50 * aDP or contigPop > 2.*aDP - minPostFixPop:  #formerly < 0.75 aDP\n",
    "        badDiscoList.append(t)\n",
    "    else: #rebuild from this big piece\n",
    "        nCanSwell +=1\n",
    "        gap = aDP - contigPop\n",
    "        origGap = gap\n",
    "        currList, addedList = contigUs.copy(), list()\n",
    "        adjoiners = getAdjoiners(currList, unitNbrs)\n",
    "        nearHDlist = [uu for uu in adjoiners]  #bias toward underused, close to HD (and its center)\n",
    "        nearHDscore = [ (unitUse[uu] - 1.) + 0.5*(unitCP[uu].distance(\n",
    "            HDpoly[t]) + unitCP[uu].distance(hdCP[t]) ) / HDdiam[t] for uu in adjoiners ] \n",
    "        stillGoing = True\n",
    "\n",
    "        while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "            idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "            while i < len(nearHDscore) and notYetPicked:        \n",
    "                listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "                unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "                canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "                if canAdd:\n",
    "                    notYetPicked = False\n",
    "                else:\n",
    "                    i +=1\n",
    "            if notYetPicked:\n",
    "                stillGoing = False  #can't add any more units without creating an enclave\n",
    "            else: #we selected the best unit to add legally\n",
    "                gap -= unitPop[unitNoToAdd]\n",
    "                addedList.append(unitNoToAdd)  #so add it to our growing HD ...\n",
    "                currList.append( unitNoToAdd)\n",
    "                for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                    if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                        nearHDlist.append(uu)\n",
    "                        nearHDscore.append((unitUse[uu] - 1.) + 0.5*(unitCP[uu].distance(\n",
    "                            HDpoly[t]) + unitCP[uu].distance(hdCP[t]) ) / HDdiam[t] )\n",
    "                del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "                del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "                for i, uu in enumerate(nearHDlist.copy()):\n",
    "                    if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                        del nearHDscore[nearHDlist.index(uu)]\n",
    "                        del nearHDlist[ nearHDlist.index(uu)]\n",
    "        for u in addedList:\n",
    "            unitUse[u] += HDweight[t] * nDistricts\n",
    "        for u in list( set(HDunitList[t]).difference(set(contigUs)) ):\n",
    "            unitUse[u] -= HDweight[t] * nDistricts       \n",
    "        HDunitList[t] = contigUs + addedList\n",
    "        HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "        HDnAddedUnits[t] = len(addedList)\n",
    "    \n",
    "badDiscoList += enclaveOnly\n",
    "print(\"we partially regrew\",nCanSwell,\"HDs, leaving\",len(badDiscoList),\"to regrow from scratch\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "f57325dd-523c-466a-80cb-8e10b739b4ac",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "previous avg use and its sd are 1.00593 0.10366\n",
      "defining and displaying current unit use after above manipulations; compare to original farther above.\n",
      "current avg use and its sd are 1.00563 0.10231\n",
      "CCB cluster 0 = unit 9675 with pop 211407.0 now has use of 1.0028222421403625\n",
      "CCB cluster 1 = unit 9676 with pop 82367.0 now has use of 1.025956822817205\n",
      "CCB cluster 2 = unit 9677 with pop 83357.0 now has use of 1.0894734270605857\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"previous avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "print(\"defining and displaying current unit use after above manipulations; compare to original farther above.\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"= unit\",u,\"with pop\",unitPop[u],\"now has use of\",unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "0ce918e1-0d30-4930-9fb8-0769d793683c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "quick classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 1000 time is now 19\n",
      "working on HD 2000 time is now 37\n",
      "working on HD 3000 time is now 53\n",
      "working on HD 4000 time is now 69\n",
      "working on HD 5002 time is now 82\n",
      "working on HD 6002 time is now 95\n",
      "working on HD 7002 time is now 109\n",
      "working on HD 8002 time is now 123\n",
      "working on HD 9002 time is now 141\n",
      "working on HD 10002 time is now 161\n",
      "out of 10082 total HDs, there were 9990.0 contiguous and 10007.0 complement-contiguous HDs\n",
      "38 HDs had both discontiguity problems, while enclave-only = 37 and discontig only= 54\n",
      "here are the histograms of the small piece and enclave list lengths, total no = 92 37\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And here are the small-HD-piece and small-enclave pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#THIS is the FINDSTILLBROKEN code\n",
    "print(\"quick classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%1000 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "\n",
    "print(\"here are the histograms of the small piece and enclave list lengths, total no =\",\n",
    "      len(smallPieceLists),len(enclaveLists) )\n",
    "plt.hist([s for s in smallPieceLengths],label=\"small piece l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.hist([e for e in enclaveLengths],label=\"enclave l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.legend()\n",
    "plt.show()\n",
    "print(\"And here are the small-HD-piece and small-enclave pops\")\n",
    "plt.hist([sum(unitPop[u] for u in s) for s in smallPieceLists],label=\"small piece 1 pop\",histtype='step')\n",
    "plt.hist([sum(unitPop[u] for u in e) for e in enclaveLists],label=\"enclave 1 pop\",histtype='step')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "463db75a-694e-4c7d-9693-e10f3b4d65db",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before addressing enclaves, let's triage the discontinuous HDs\n",
      "Now work on dropping smallish disconnected pieces that would keep us above 715993 district pop vs 753676 target\n",
      "we'll also trim any HD with total islands' pop <= 15073\n",
      "working on HD 316\n",
      "Out of 92 discontig HDs 92 had discontig HDs.\n",
      "Of these, 8 won't be under 715993 after all minor discontigys were shed, while 84 would be too underpopped if we trimmed the discontig pieces\n",
      "here is adjusted pop by original pop for those we trimmed and those we didn't (x)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, reclassify after the trimming\n",
      "There are 84 HDs still with both discontinuity problems\n",
      "Additionally, 0 of the originally discontig HDs are now contig but still have an enclave\n"
     ]
    }
   ],
   "source": [
    "print(\"Before addressing enclaves, let's triage the discontinuous HDs\")\n",
    "#this is the CANTRIM code####\n",
    "\n",
    "#for t in sPgenerator:\n",
    "#    isContig, smallP = isContiguous(filledHDvtdList[t],unitNbrs)\n",
    "#    if isContig:\n",
    "#        print(\"oops!\",t)\n",
    "maxNudgeDownPop = int(0.02 * aDP)\n",
    "minPostFixPop = int(0.95 * aDP)\n",
    "print(\"Now work on dropping smallish disconnected pieces that would keep us above\",minPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "print(\"we'll also trim any HD with total islands' pop <=\",maxNudgeDownPop)\n",
    "nOrigIslands = [0 for t in range(nHDs)]\n",
    "totalIslandPop = [0. for t in range(nHDs)]\n",
    "tryToTrim, canTrim, cantTrim = list(), list(), list()\n",
    "for jj, t in enumerate(sPgenerator):\n",
    "    if jj%100 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    currList, shedList, shedPop = HDunitList[t].copy(), list(),  0.\n",
    "    done,newList = isContiguous(currList,unitNbrs)\n",
    "    if not done:\n",
    "        tryToTrim.append(t)\n",
    "        while not done:\n",
    "            shedList += newList\n",
    "            shedPop += np.sum( [unitPop[u] for u in newList] )\n",
    "            currList = list (  set(currList).difference(set(newList ))  )\n",
    "            done, newList = isContiguous(currList, unitNbrs)\n",
    "            nOrigIslands[t] +=1\n",
    "            \n",
    "        totalIslandPop[t] = shedPop            \n",
    "        if shedPop <= maxNudgeDownPop or HDvPop[t] - shedPop >= minPostFixPop:\n",
    "            canTrim.append(t)\n",
    "            HDvPop[t] -= shedPop\n",
    "            HDunitList[t] = list (set(HDunitList[t]).difference(set(shedList)) )\n",
    "        else:\n",
    "            cantTrim.append(t)\n",
    "print(\"Out of\",len(sPgenerator),\"discontig HDs\",len(tryToTrim),\"had discontig HDs.\")\n",
    "print(\"Of these,\",len(canTrim),\"won't be under\",minPostFixPop,\"after all minor discontigys were shed, while\",\n",
    "      len(cantTrim),\"would be too underpopped if we trimmed the discontig pieces\")\n",
    "plt.scatter([HDvPop[t] + totalIslandPop[t] for t in canTrim],[HDvPop[t] for t in canTrim])\n",
    "plt.scatter([HDvPop[t]                     for t in cantTrim],[HDvPop[t] for t in cantTrim],marker=\"x\")\n",
    "print(\"here is adjusted pop by original pop for those we trimmed and those we didn't (x)\")\n",
    "plt.plot([0.9*aDP, 1.1*aDP],[aDP, aDP], ls=\"--\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Now, reclassify after the trimming\")\n",
    "badDiscoList, stillHasEnclave = list(), list()\n",
    "for t in sPgenerator:    \n",
    "    unbroken, noEnclave, __, ____ = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if not unbroken:\n",
    "        badDiscoList.append(t)  #will do a major triage on these later\n",
    "    if unbroken and not noEnclave:\n",
    "        stillHasEnclave.append(t)\n",
    "print(\"There are\",len(badDiscoList),\"HDs still with both discontinuity problems\")\n",
    "print(\"Additionally,\",len(stillHasEnclave),\"of the originally discontig HDs are now contig but still have an enclave\")\n",
    "eLgenerator += stillHasEnclave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "39d37c15-759f-462c-b503-047b6b5e1554",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "103 172 84\n",
      "{3584, 2056, 7688, 7690, 2065, 2066, 2069, 2072, 2073, 32, 9761, 1058, 1571, 37, 38, 9766, 6701, 6702, 9777, 6706, 5683, 5685, 6199, 9791, 9792, 8770, 8771, 8774, 7241, 9801, 7754, 9803, 8778, 8779, 9814, 5719, 6744, 1118, 4703, 4196, 4197, 4199, 7788, 5233, 7796, 134, 135, 138, 4240, 4752, 5266, 2707, 7825, 151, 5276, 9372, 1695, 9376, 9379, 5284, 9380, 9383, 1704, 3242, 3243, 9386, 9388, 7342, 9389, 9390, 5298, 9394, 7348, 9395, 9396, 9397, 6837, 694, 4796, 3781, 2251, 8909, 2259, 215, 729, 743, 748, 9967, 752, 9968, 9972, 759, 767, 9991, 5899, 2832, 10000, 10011, 6940, 4902, 5928, 300, 2861, 5933, 303, 2863, 4912, 6451, 4916, 2869, 2870, 7479, 824, 7481, 314, 2873, 4412, 7484, 5941, 4415, 320, 7489, 827, 9539, 6468, 831, 6983, 10038, 10055, 5962, 10061, 10066, 3923, 3926, 3928, 3930, 4443, 4955, 7004, 10077, 4447, 3931, 3933, 4453, 4456, 6507, 2925, 4463, 5487, 6513, 6511, 6514, 9586, 881, 3961, 2942, 9603, 9604, 9613, 5006, 6033, 1944, 5018, 2460, 9629, 9630, 5023, 4513, 4514, 2978, 2979, 2981, 431, 4024, 5569, 7106, 6086, 6101, 5594, 3036, 3037, 1503, 1504, 9696, 9697, 6120, 5611, 5101, 5617, 5106, 7668}\n"
     ]
    }
   ],
   "source": [
    "print(len(discontigOnly),len(bothProblems), len(badDiscoList))\n",
    "print((set(discontigOnly).union(set(bothProblems)) ) .difference(set(badDiscoList)) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "2e54bac4-c327-473d-bbb4-257486bddd20",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And now, the major disco'd HDs (< 0.75 aDP in HDcP-contig portion and/or enclaves).  Redraw fully using HDswell\n",
      "Assuming we have run the previous canSwell block.  This block repeats the code, but starting from the home unit\n",
      "This takes 1 - 1000 sec per HD :-( The total number of HDs to fix is 84\n",
      "swell-generating HD 4723 our 1 th HD we must regrow out of 84 0 sec elapsed\n",
      "swell-generating HD 5363 our 11 th HD we must regrow out of 84 3691 sec elapsed\n",
      "swell-generating HD 6937 our 21 th HD we must regrow out of 84 8257 sec elapsed\n",
      "swell-generating HD 9460 our 31 th HD we must regrow out of 84 12762 sec elapsed\n",
      "swell-generating HD 10023 our 41 th HD we must regrow out of 84 30096 sec elapsed\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[84], line 38\u001b[0m\n\u001b[0;32m     36\u001b[0m listNo \u001b[38;5;241m=\u001b[39m idx[i]   \u001b[38;5;66;03m#nearHDscore.index(np.min(nearHDscore))\u001b[39;00m\n\u001b[0;32m     37\u001b[0m unitNoToAdd \u001b[38;5;241m=\u001b[39m nearHDlist[listNo]  \u001b[38;5;66;03m#add this unit ...\u001b[39;00m\n\u001b[1;32m---> 38\u001b[0m canAdd  \u001b[38;5;241m=\u001b[39m \u001b[43mwontEnclave\u001b[49m\u001b[43m(\u001b[49m\u001b[43munitNoToAdd\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcurrList\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43munitNbrs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mborderUnits\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     39\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m canAdd:\n\u001b[0;32m     40\u001b[0m     notYetPicked \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n",
      "Cell \u001b[1;32mIn[2], line 879\u001b[0m, in \u001b[0;36mwontEnclave\u001b[1;34m(proposedU, dList, NBRLIST, mapBDRYLIST)\u001b[0m\n\u001b[0;32m    877\u001b[0m                 adjSet \u001b[38;5;241m=\u001b[39m adjSet\u001b[38;5;241m.\u001b[39munion( \u001b[38;5;28mset\u001b[39m(NBRLIST[UU])\u001b[38;5;241m.\u001b[39mdifference(\u001b[38;5;28mset\u001b[39m(newList)) )\n\u001b[0;32m    878\u001b[0m             ADJLIST \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(adjSet)\n\u001b[1;32m--> 879\u001b[0m             wontEnclave, __ \u001b[38;5;241m=\u001b[39m   \u001b[43misContiguous\u001b[49m\u001b[43m(\u001b[49m\u001b[43mADJLIST\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mNBRLIST\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    881\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m wontEnclave\n",
      "Cell \u001b[1;32mIn[2], line 688\u001b[0m, in \u001b[0;36misContiguous\u001b[1;34m(VLIST, NEIGHBORLIST, returnBiggestPiece)\u001b[0m\n\u001b[0;32m    686\u001b[0m             \u001b[38;5;28;01mif\u001b[39;00m VV \u001b[38;5;129;01min\u001b[39;00m VLIST \u001b[38;5;129;01mand\u001b[39;00m VV \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m foundList:\n\u001b[0;32m    687\u001b[0m                 newList\u001b[38;5;241m.\u001b[39mappend(VV)\n\u001b[1;32m--> 688\u001b[0m                 \u001b[43mfoundList\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mappend\u001b[49m\u001b[43m(\u001b[49m\u001b[43mVV\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    689\u001b[0m     prevList \u001b[38;5;241m=\u001b[39m newList\u001b[38;5;241m.\u001b[39mcopy()      \n\u001b[0;32m    690\u001b[0m pickedPieceList \u001b[38;5;241m=\u001b[39m foundList\u001b[38;5;241m.\u001b[39mcopy()  \u001b[38;5;66;03m#default contiguous sublist to pass back to main\u001b[39;00m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "#THIS IS THE MUSTSPAWN code block\n",
    "#                  ****** ERRONEOUSLY ONLY DOES BADDISCOLIST[38:]\n",
    "\n",
    "print(\"And now, the major disco'd HDs (< 0.75 aDP in HDcP-contig portion and/or enclaves).  Redraw fully using HDswell\")\n",
    "print(\"Assuming we have run the previous canSwell block.  This block repeats the code, but starting from the home unit\")\n",
    "print(\"This takes 1 - 1000 sec per HD :-( The total number of HDs to fix is\",len(badDiscoList))\n",
    "avgDiam = MAP.area**0.5 / float(nDistricts)\n",
    "startTime = time.time()\n",
    "for iii,t in enumerate(badDiscoList[38:]):  #MO -- restarted\n",
    "    if iii%10 == 0:\n",
    "        print(\"swell-generating HD\",t,\"our\",iii+1,\"th HD we must regrow out of\",len(badDiscoList),int(time.time()-startTime),\"sec elapsed\" )\n",
    "    notInCluster = True\n",
    "    for jj, geo in enumerate(CCBgeom):  #swell in-corner HDs from the corner cluster\n",
    "        if geo.contains(hdCP[t]):\n",
    "            starterU = allUnits.index(jj+0.25)\n",
    "            notInCluster = False\n",
    "    if notInCluster:\n",
    "        distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "        starterU = HDunitList[t][distList.index(np.min(distList))]  #starter = unit with centroid closest to the hd center\n",
    "    contigUs = [starterU]  #we used getContigFromStarter(starterU, HDunitList[t], unitNbrs) in above code block\n",
    "    altContigUs = getContigFromStarter(starterU, HDunitList[t], unitNbrs)\n",
    "    altContigPop = np.sum( [ unitPop[u] for u in altContigUs ] )\n",
    "    if abs( altContigPop/aDP - 1.0) < 0.4 : #MO and later -- MAKING THIS MORE LENIENT; only regrow from scratch if contig pop > 40% off\n",
    "        contigUs = altContigUs.copy()\n",
    "    contigPop = np.sum( [ unitPop[u] for u in contigUs ] )\n",
    "    gap = aDP - contigPop\n",
    "    origGap = gap\n",
    "    currList, addedList = contigUs.copy(), list()\n",
    "    adjoiners = getAdjoiners(currList, unitNbrs)\n",
    "    nearHDlist = [uu for uu in adjoiners]  #bias toward underused, close to HD (and its center)\n",
    "    nearHDscore = [ (0.2*(unitUse[uu] - 1.) ) + 0.5*(unitCP[uu].distance(HDpoly[t]) + \n",
    "        unitCP[uu].distance(hdCP[t])  )  / HDdiam[t] for uu in adjoiners ]\n",
    "    stillGoing = True\n",
    "    \n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd:\n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else: #we selected the best unit to add legally\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((0.1*(unitUse[uu] - 1.) ) + 0.5*(unitCP[uu].distance(HDpoly[t]) + \n",
    "                                                                        unitCP[uu].distance(hdCP[t])  )  / HDdiam[t] )\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    for u in list( set(HDunitList[t]).difference(set(contigUs)) ):\n",
    "        unitUse[u] -= HDweight[t] * nDistricts       \n",
    "    HDunitList[t] = contigUs + addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    HDnAddedUnits[t] = len(addedList)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "2290067b-f260-4511-8bdd-dd6481100ff4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "43 10083 84\n"
     ]
    }
   ],
   "source": [
    "#NOTE - was working on another state in parallel with some of above block\n",
    "#stop, restart below in case we have locked up\n",
    "print(iii, t, len(badDiscoList))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "aed538f4-722d-4693-948e-20989da49fbd",
   "metadata": {},
   "outputs": [],
   "source": [
    "nHDs = 10084"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d5a2b93c-ec5a-4264-82ee-60fa14447311",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"IL only -- intermediate save \")\n",
    "HDvPop = [0. for t in range(nHDs)]\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"opt3mostlyContigButOffPop.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "318098a2-b495-4279-991e-3981f49479b6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this optional RESTART block pulls in an existing UNIT (not vtd) list for squaring up\n",
      "Must have already established unitGeoms, pops, topology in above blocks\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the unpatched UNIT list file, e.g. ./2024state_HD_output/IL10084opt3ContigButOffPopUnit.csv ./2024state_HD_output/IL10084opt3mostlyContigButOffPop.csv\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sum of HDweight should be unity, actually is 0.9999999999998778\n",
      "I will now renormalize\n",
      "normalized weight is now 1.0\n",
      "I read in 10084 HD lists of units\n",
      "weighted unit use histogram\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on avg unit-to-HDcp dist for HD 0\n",
      "working on avg unit-to-HDcp dist for HD 800\n",
      "working on avg unit-to-HDcp dist for HD 1600\n",
      "working on avg unit-to-HDcp dist for HD 2400\n",
      "working on avg unit-to-HDcp dist for HD 3200\n",
      "working on avg unit-to-HDcp dist for HD 4000\n",
      "working on avg unit-to-HDcp dist for HD 4800\n",
      "working on avg unit-to-HDcp dist for HD 5602\n",
      "working on avg unit-to-HDcp dist for HD 6402\n",
      "working on avg unit-to-HDcp dist for HD 7202\n",
      "working on avg unit-to-HDcp dist for HD 8002\n",
      "working on avg unit-to-HDcp dist for HD 8802\n",
      "working on avg unit-to-HDcp dist for HD 9602\n"
     ]
    }
   ],
   "source": [
    "#restart pick up from here next day - triage, swell remaining ....\n",
    "print(\"this optional RESTART block pulls in an existing UNIT (not vtd) list for squaring up\") \n",
    "print(\"Must have already established unitGeoms, pops, topology in above blocks\")\n",
    "guessedFile = \"enter the unpatched UNIT list file, e.g. ./2024state_HD_output/\"+STATE+str(nHDs)+\"opt3ContigButOffPopUnit.csv\"\n",
    "infile = input(guessedFile)\n",
    "inDF = pd.read_csv(infile)\n",
    "vtdListString = inDF[\"HDunitList\"]  #inDF[\"HDvtdList\"]\n",
    "nHDs = len(vtdListString)\n",
    "inVTDlist = [ast.literal_eval(vtdListString[t]) for t in range(nHDs)]\n",
    "HDweight = inDF[\"HDweight\"]\n",
    "sumWt = np.sum(HDweight)\n",
    "print(\"sum of HDweight should be unity, actually is\",sumWt)\n",
    "print(\"I will now renormalize\")\n",
    "HDweight = [HDweight[t] /sumWt for t in range(nHDs)]\n",
    "print(\"normalized weight is now\",np.sum(HDweight))\n",
    "HDvPop = inDF[\"HDvPop\"].to_list()\n",
    "hdCPx, hdCPy = inDF[\"centroid x\"], inDF[\"centroid y\"]\n",
    "hdCP = [Point(hdCPx[t], hdCPy[t]) for t in range(nHDs)]\n",
    "print(\"I read in\",nHDs,\"HD lists of units\") #vtds\")\n",
    "HDunitList = [inVTDlist[t].copy() for t in range(nHDs)]\n",
    "unitUse = [0. for u in range(nUnits) ]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse,weights = unitPop)\n",
    "print(\"weighted unit use histogram\")\n",
    "plt.show()\n",
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "popHDlist = list()\n",
    "for t in range(nHDs):\n",
    "    if len(HDunitList[t]) > 0:\n",
    "        popHDlist.append(t)\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%800 == 0:\n",
    "        print(\"working on avg unit-to-HDcp dist for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "c1b66c69-a0d5-4222-be34-fe0bd21ab6e8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(not-so-)final check -- any more disco's ?\n",
      "working on HD 0 time is now 0 sec\n",
      "working on HD 500 time is now 18 sec\n",
      "working on HD 1000 time is now 28 sec\n",
      "working on HD 1500 time is now 34 sec\n",
      "working on HD 2000 time is now 58 sec\n",
      "working on HD 2500 time is now 80 sec\n",
      "working on HD 3000 time is now 108 sec\n",
      "working on HD 3500 time is now 128 sec\n",
      "working on HD 4000 time is now 133 sec\n",
      "working on HD 4500 time is now 142 sec\n",
      "working on HD 5002 time is now 150 sec\n",
      "working on HD 5502 time is now 154 sec\n",
      "working on HD 6002 time is now 159 sec\n",
      "working on HD 6502 time is now 164 sec\n",
      "working on HD 7002 time is now 168 sec\n",
      "working on HD 7502 time is now 173 sec\n",
      "working on HD 8002 time is now 178 sec\n",
      "working on HD 8502 time is now 184 sec\n",
      "working on HD 9002 time is now 203 sec\n",
      "working on HD 9502 time is now 254 sec\n",
      "working on HD 10002 time is now 291 sec\n",
      "out of 10082 total HDs, there were 10029 9 37 7 HDs that were clean, discontig only, enclave-only, both problems after triage\n",
      "this took 301 seconds with maxLoop =  5\n"
     ]
    }
   ],
   "source": [
    "print(\"(not-so-)final check -- any more disco's ?\")\n",
    "maxLOOP = 5  #can increase to avoid false enclave detection\n",
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%500 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime),\"sec\")\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs, maxLOOP)\n",
    "    if not noEnclave:\n",
    "        noEnclave, enclaveList = isContiguous(list({u for u in range(nUnits)}.difference(set(HDunitList[t]))),unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems after triage\")\n",
    "print(\"this took\",int(time.time() - startTime),\"seconds with maxLoop = \", maxLOOP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "70a788e5-8a54-499a-bbb9-793d39a3e7c9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's fill in all enclaves that won't put us over 791360 district pop vs 753676 target\n",
      "working on enclave-y HD 32 . We have evaluated 0 of 37 enclavy HDs.Time is now 0\n",
      "Out of 37 HDs identified as enclave-only 37 had enclaves.\n",
      "Of these, 37 wouldn't be over 791360 if all enclaves filled, while 0 were too populous\n",
      "here is enclave pop by final pop for those we filled\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### THIS IS THE \"CANFILL\" CODE  #check if sum of enclave pops small enough to add\n",
    "maxNudgeUpPop = int(0.02 * aDP)\n",
    "maxPostFixPop = int(1.05 * aDP)\n",
    "print(\"Now, let's fill in all enclaves that won't put us over\",maxPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "nOrigEnclaves = [0 for t in range(nHDs)]\n",
    "totalEnclavePop = [0. for t in range(nHDs)]\n",
    "tryToFill, canFill, cantFill = list(), list(), list()\n",
    "startTime = time.time()  #takes about xx sec per HD triage\n",
    "        \n",
    "for iii, t in enumerate(enclaveOnly):\n",
    "    if iii%50 == 0:\n",
    "        print(\"working on enclave-y HD\",t,\". We have evaluated\",iii,\"of\",len(enclaveOnly),\"enclavy HDs.Time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and not noEnclave:  #\"and unbroken\" new 1/15 - discontig HDs will usually appear to have enclaves.  We'll fix these in later block\n",
    "        tryToFill.append(t)\n",
    "        enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "        nOrigEnclaves[t] = len(enclaveLists)\n",
    "        totalEnclavePop[t] = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in enclaveLists ] ) \n",
    "        if HDvPop[t] + totalEnclavePop[t] <= maxPostFixPop or totalEnclavePop[t] < maxNudgeUpPop:\n",
    "            canFill.append(t)\n",
    "            for eL in enclaveLists:\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += np.sum([unitPop[u] for u in eL])\n",
    "        else:\n",
    "            cantFill.append(t)\n",
    "print(\"Out of\",len(enclaveOnly),\"HDs identified as enclave-only\",len(tryToFill),\"had enclaves.\")\n",
    "print(\"Of these,\",len(canFill),\"wouldn't be over\",maxPostFixPop,\"if all enclaves filled, while\",len(cantFill),\"were too populous\")\n",
    "plt.scatter([HDvPop[t] for t in canFill],[totalEnclavePop[t] for t in canFill])\n",
    "print(\"here is enclave pop by final pop for those we filled\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "653826fd-0c3b-433e-8fd2-717100d961a9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, reclassify after the trimming\n",
      "We still have 0 HDs that are contig but with an enclave\n",
      "There are now 16 noncontiguous HDs\n"
     ]
    }
   ],
   "source": [
    "print(\"Now, reclassify after the trimming\")\n",
    "badDiscoList, stillHasEnclave = list(), list()\n",
    "for t in enclaveOnly + discontigOnly + bothProblems :    \n",
    "    unbroken, noEnclave, __, ____ = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if not unbroken:\n",
    "        badDiscoList.append(t)  #will do a major triage on these later\n",
    "    if unbroken and not noEnclave:\n",
    "        stillHasEnclave.append(t)\n",
    "print(\"We still have\",len(stillHasEnclave),\"HDs that are contig but with an enclave\")\n",
    "print(\"There are now\",len(badDiscoList),\"noncontiguous HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "ee15cbbf-d1a7-4855-bd17-0ec440bb4d54",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "how far off are the pops for the remaining discontig'ers?\n",
      "switcheroo for 3909\n",
      "t,pop/aDP,contigPop/aDP 3909 0.999 0.708\n",
      "switcheroo for 3963\n",
      "t,pop/aDP,contigPop/aDP 3963 1.0 0.362\n",
      "switcheroo for 4004\n",
      "t,pop/aDP,contigPop/aDP 4004 0.999 0.915\n",
      "switcheroo for 4254\n",
      "t,pop/aDP,contigPop/aDP 4254 0.798 0.007\n",
      "switcheroo for 4709\n",
      "t,pop/aDP,contigPop/aDP 4709 0.999 0.856\n",
      "switcheroo for 4714\n",
      "t,pop/aDP,contigPop/aDP 4714 1.0 0.824\n",
      "switcheroo for 4721\n",
      "t,pop/aDP,contigPop/aDP 4721 1.0 0.87\n",
      "switcheroo for 10052\n",
      "t,pop/aDP,contigPop/aDP 10052 0.907 0.807\n",
      "switcheroo for 10071\n",
      "t,pop/aDP,contigPop/aDP 10071 0.901 0.829\n",
      "switcheroo for 1964\n",
      "t,pop/aDP,contigPop/aDP 1964 0.931 0.874\n",
      "switcheroo for 1965\n",
      "t,pop/aDP,contigPop/aDP 1965 0.916 0.833\n",
      "switcheroo for 2184\n",
      "t,pop/aDP,contigPop/aDP 2184 0.966 0.826\n",
      "switcheroo for 2185\n",
      "t,pop/aDP,contigPop/aDP 2185 0.965 0.848\n",
      "switcheroo for 2213\n",
      "t,pop/aDP,contigPop/aDP 2213 0.965 0.773\n",
      "switcheroo for 3034\n",
      "t,pop/aDP,contigPop/aDP 3034 1.203 0.802\n",
      "switcheroo for 10070\n",
      "t,pop/aDP,contigPop/aDP 10070 0.924 0.72\n"
     ]
    }
   ],
   "source": [
    "print(\"how far off are the pops for the remaining discontig'ers?\")\n",
    "badContigUlists = list()\n",
    "for t in badDiscoList:\n",
    "    notInCluster = True\n",
    "    for jj, geo in enumerate(CCBgeom):  #swell in-corner HDs from the corner cluster\n",
    "        if geo.contains(hdCP[t]):\n",
    "            starterU = allUnits.index(jj+0.25)\n",
    "            notInCluster = False\n",
    "            print(\"t starts in CCB\",jj)\n",
    "    if notInCluster:\n",
    "        distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "        starterU = HDunitList[t][distList.index(np.min(distList))]  #starter = unit with centroid closest to the hd center\n",
    "    altContigUs = getContigFromStarter(starterU, HDunitList[t], unitNbrs)\n",
    "    altContigPop = np.sum( [ unitPop[u] for u in altContigUs ] )\n",
    "    if altContigPop < 0.5 * aDP:\n",
    "        print(\"switcheroo for\",t)\n",
    "        otherUs = list(set(HDunitList[t]).difference(set(altContigUs)))        \n",
    "        altContigUs = getContigFromStarter(otherUs[0], HDunitList[t], unitNbrs)\n",
    "        altContigPop = np.sum( [ unitPop[u] for u in altContigUs ] )\n",
    "    print(\"t,pop/aDP,contigPop/aDP\",t,r3(HDvPop[t]/aDP), r3(altContigPop/aDP) )\n",
    "    badContigUlists.append(altContigUs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "0e336151-4833-4a0d-af72-2878900c7361",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t = badDiscoList[3]\n",
    "for u in HDunitList[t]:\n",
    "    plotPoly(unitGeom[u],0.12)\n",
    "    if u in borderSet:\n",
    "        for uu in set(unitNbrs[u]).intersection(borderSet).difference(set(HDunitList[t])):\n",
    "            plotPoly(unitGeom[uu])\n",
    "plotPoly(hdCP[t].buffer(0.1))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "47c6ba0a-7fcf-4f18-b75a-3a58c39f8f18",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "IL only -- intermediate save 2 \n"
     ]
    }
   ],
   "source": [
    "print(\"IL only -- intermediate save 2 \")\n",
    "HDvPop = [0. for t in range(nHDs)]\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"opt3mostlyContigButOffPop2.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "6458ad56-8188-41e0-aa14-0a41d0b206a9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we will divide these into border-bridgers and re-swellers (too much to bridge)\n",
      "The bridging code will be copied from Indiana\n",
      "3909 contiguity is now True\n",
      "3909 updated pop is now / aDP 1.0039\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3963 contiguity is now False\n",
      "contig still fails for HD 3963\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4004 contiguity is now True\n",
      "4004 updated pop is now / aDP 1.00045\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4714 contiguity is now False\n",
      "contig still fails for HD 4714\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10052 contiguity is now True\n",
      "10052 updated pop is now / aDP 0.91972\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10071 contiguity is now True\n",
      "10071 updated pop is now / aDP 0.91139\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1965 contiguity is now False\n",
      "contig still fails for HD 1965\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2184 contiguity is now False\n",
      "contig still fails for HD 2184\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2185 contiguity is now False\n",
      "contig still fails for HD 2185\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2213 contiguity is now False\n",
      "contig still fails for HD 2213\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3034 contiguity is now False\n",
      "contig still fails for HD 3034\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10070 contiguity is now True\n",
      "10070 updated pop is now / aDP 0.92561\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"we will divide these into border-bridgers and re-swellers (too much to bridge)\")\n",
    "print(\"The bridging code will be copied from Indiana\")\n",
    "bridgerIndices = [0,1,2,5,7,8, 10,11,12,13,14,15]\n",
    "reswellers = [3,4,6,9]\n",
    "bridgerList, reswellerList = list(), list()\n",
    "for i,t in enumerate(badDiscoList):\n",
    "    if i in bridgerIndices:\n",
    "        bridgerList.append(t)\n",
    "    else:\n",
    "        reswellerList.append(t)\n",
    "for t in bridgerList :  \n",
    "    borderBridgers, bridgeStarters = list(), list()\n",
    "    for u in set(HDunitList[t]).intersection(borderSet) :\n",
    "        borderNeighbors = list((set(unitNbrs[u]).intersection(borderSet)).difference(set(HDunitList[t]) ) )\n",
    "        nBorderNeighbors = len(borderNeighbors  )\n",
    "        if nBorderNeighbors == 1:  #this is an \"open\" HD border unit that adjoins a non-HD border\n",
    "            borderBridgers.append(u)\n",
    "            bridgeStarters.append(borderNeighbors[0])\n",
    "    foundBridge = False\n",
    "    bridgeChains = [[u, bridgeStarters[i]] for i,u in enumerate(borderBridgers)]\n",
    "    while not foundBridge:\n",
    "        for i, chain in enumerate(bridgeChains):\n",
    "            u = chain[-1]\n",
    "            newLink = list( set(unitNbrs[u]).intersection(borderSet.difference(bridgeChains[i]) ) )[0]\n",
    "            if newLink in HDunitList[t]:\n",
    "                foundBridge = True\n",
    "                addedList = bridgeChains[i].copy()\n",
    "                break\n",
    "            else:\n",
    "                bridgeChains[i].append(newLink )\n",
    "    for u in HDunitList[t]:\n",
    "        plotPoly(unitGeom[u],0.3)\n",
    "    for u in addedList:\n",
    "        plotPoly(unitGeom[u],1.5)\n",
    "    plotPoly(hdCP[t].buffer(0.5))\n",
    "    newList = list(set(HDunitList[t]).union(set(addedList)) )\n",
    "    contig = isContiguous(newList,unitNbrs)[0]\n",
    "    print(t,\"contiguity is now\", contig)\n",
    "    if contig:\n",
    "        HDunitList[t] = newList.copy()\n",
    "        HDvPop[t] = np.sum([unitPop[u] for u in HDunitList[t] ])\n",
    "        print(t, \"updated pop is now / aDP\",r5(HDvPop[t] / aDP) )\n",
    "    else:\n",
    "        print(\"contig still fails for HD\",t)\n",
    "    plt.show()\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "fcabdc40-91e6-4675-9953-2416f6ab341b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "t,unbroken, noEnclave 3909 True True\n",
      "t,unbroken, noEnclave 3963 True True\n",
      "t,unbroken, noEnclave 4004 True True\n",
      "t,unbroken, noEnclave 4254 True True\n",
      "t,unbroken, noEnclave 4709 True True\n",
      "t,unbroken, noEnclave 4714 True True\n",
      "t,unbroken, noEnclave 4721 True True\n",
      "t,unbroken, noEnclave 10052 True True\n",
      "t,unbroken, noEnclave 10071 True True\n",
      "t,unbroken, noEnclave 1964 False False\n",
      "t,unbroken, noEnclave 1965 False False\n",
      "t,unbroken, noEnclave 2184 False False\n",
      "t,unbroken, noEnclave 2185 False False\n",
      "t,unbroken, noEnclave 2213 False False\n",
      "t,unbroken, noEnclave 3034 False False\n",
      "t,unbroken, noEnclave 10070 True False\n"
     ]
    }
   ],
   "source": [
    "toSwell = list()  #note: below rerun after I fixed some\n",
    "for t in badDiscoList:\n",
    "    unbroken, noEnclave, __, ____ = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    print(\"t,unbroken, noEnclave\",t,unbroken,noEnclave)\n",
    "    if not (unbroken and noEnclave):\n",
    "        toSwell.append(t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c5d3bcbc-8203-410b-a797-5f9c9cea720f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "9a34ac87-d3f8-498b-a595-6909d2ed900f",
   "metadata": {},
   "outputs": [],
   "source": [
    "HDpoly = hdCP.copy()\n",
    "for t in toSwell:\n",
    "    for u in HDunitList[t]:\n",
    "        HDpoly[t] = HDpoly[t].union(unitGeom[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "4ca9ccad-66ec-49cb-b5f0-3794a5d3a736",
   "metadata": {},
   "outputs": [],
   "source": [
    "HDdiam = [1. for t in range(nHDs)]\n",
    "for t in toSwell:\n",
    "    HDdiam[t] = HDpoly[t].area **0.5\n",
    "maxGap = 0.9 * np.median(unitPop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "5b628699-afb0-4094-84d7-2fe0051f570e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And now, the major disco'd HDs (< 0.75 aDP in HDcP-contig portion and/or enclaves).  Redraw fully using HDswell\n",
      "Assuming we have run the previous canSwell block.  This block repeats the code, but starting from the home unit\n",
      "This takes 1 - 1000 sec per HD :-( The total number of HDs to fix is 7\n",
      "swell-generating HD 1964 our 1 th HD we must regrow out of 7 0 sec elapsed\n",
      "swell-generating HD 2185 our 4 th HD we must regrow out of 7 2276 sec elapsed\n",
      "swell-generating HD 10070 our 7 th HD we must regrow out of 7 5997 sec elapsed\n"
     ]
    }
   ],
   "source": [
    "#FOR IL ONLY -- RUN AGAIN TO CATCH THE ONES WE MISSED ABOVE\n",
    "\n",
    "#THIS IS THE MUSTSPAWN code block\n",
    "print(\"And now, the major disco'd HDs (< 0.75 aDP in HDcP-contig portion and/or enclaves).  Redraw fully using HDswell\")\n",
    "print(\"Assuming we have run the previous canSwell block.  This block repeats the code, but starting from the home unit\")\n",
    "print(\"This takes 1 - 1000 sec per HD :-( The total number of HDs to fix is\",len(toSwell))\n",
    "avgDiam = MAP.area**0.5 / float(nDistricts)\n",
    "startTime = time.time()\n",
    "for iii,t in enumerate(toSwell): \n",
    "    if iii%3 == 0:\n",
    "        print(\"swell-generating HD\",t,\"our\",iii+1,\"th HD we must regrow out of\",len(toSwell),int(time.time()-startTime),\"sec elapsed\" )\n",
    "    notInCluster = True\n",
    "    for jj, geo in enumerate(CCBgeom):  #swell in-corner HDs from the corner cluster\n",
    "        if geo.contains(hdCP[t]):\n",
    "            starterU = allUnits.index(jj+0.25)\n",
    "            notInCluster = False\n",
    "    if notInCluster:\n",
    "        distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "        starterU = HDunitList[t][distList.index(np.min(distList))]  #starter = unit with centroid closest to the hd center\n",
    "    contigUs = [starterU]  #we used getContigFromStarter(starterU, HDunitList[t], unitNbrs) in above code block\n",
    "    altContigUs = getContigFromStarter(starterU, HDunitList[t], unitNbrs)\n",
    "    altContigPop = np.sum( [ unitPop[u] for u in altContigUs ] )\n",
    "    if 1 == 1: #abs( altContigPop/aDP - 1.0) < 0.4 : #IL is slow; don't grow from scratch\n",
    "        contigUs = altContigUs.copy()\n",
    "    contigPop = np.sum( [ unitPop[u] for u in contigUs ] )\n",
    "    gap = aDP - contigPop\n",
    "    origGap = gap\n",
    "    currList, addedList = contigUs.copy(), list()\n",
    "    adjoiners = getAdjoiners(currList, unitNbrs)\n",
    "    nearHDlist = [uu for uu in adjoiners]  #bias toward underused, close to HD (and its center)\n",
    "    nearHDscore = [ (0.2*(unitUse[uu] - 1.) ) + 0.5*(unitCP[uu].distance(HDpoly[t]) + \n",
    "        unitCP[uu].distance(hdCP[t])  )  / HDdiam[t] for uu in adjoiners ]\n",
    "    stillGoing = True\n",
    "    \n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd:\n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else: #we selected the best unit to add legally\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((0.1*(unitUse[uu] - 1.) ) + 0.5*(unitCP[uu].distance(HDpoly[t]) + \n",
    "                                                                        unitCP[uu].distance(hdCP[t])  )  / HDdiam[t] )\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    for u in list( set(HDunitList[t]).difference(set(contigUs)) ):\n",
    "        unitUse[u] -= HDweight[t] * nDistricts       \n",
    "    HDunitList[t] = contigUs + addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    #HDnAddedUnits[t] = len(addedList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "8b649aeb-bdb1-4b8d-b04a-c30860c8797a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "IL only -- intermediate save 3 \n"
     ]
    }
   ],
   "source": [
    "print(\"IL only -- intermediate save 3 \")\n",
    "HDvPop = [0. for t in range(nHDs)]\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"opt3mostlyContigButOffPop3.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "b3b680bc-796f-4401-b9ea-11b231bf4cca",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "t,unbroken, noEnclave 3909 True True\n",
      "t,unbroken, noEnclave 3963 True True\n",
      "t,unbroken, noEnclave 4004 True True\n",
      "t,unbroken, noEnclave 4254 True True\n",
      "t,unbroken, noEnclave 4709 True True\n",
      "t,unbroken, noEnclave 4714 True True\n",
      "t,unbroken, noEnclave 4721 True True\n",
      "t,unbroken, noEnclave 10052 True True\n",
      "t,unbroken, noEnclave 10071 True True\n",
      "t,unbroken, noEnclave 1964 True True\n",
      "t,unbroken, noEnclave 1965 True True\n",
      "t,unbroken, noEnclave 2184 True True\n",
      "t,unbroken, noEnclave 2185 True True\n",
      "t,unbroken, noEnclave 2213 True True\n",
      "t,unbroken, noEnclave 3034 True True\n",
      "t,unbroken, noEnclave 10070 True True\n"
     ]
    }
   ],
   "source": [
    "toSwell = list()  #note: below rerun after I fixed some\n",
    "for t in badDiscoList:\n",
    "    unbroken, noEnclave, __, ____ = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    print(\"t,unbroken, noEnclave\",t,unbroken,noEnclave)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ba2a282d-24d0-4e9c-9c94-be413ad93369",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "42ddb4c6-a84a-45ec-be3e-bb9d1af51e20",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(not-so-)final check -- any more disco's ?\n",
      "working on HD 0 time is now 0 sec\n",
      "working on HD 500 time is now 5 sec\n",
      "working on HD 1000 time is now 12 sec\n",
      "working on HD 1500 time is now 17 sec\n",
      "working on HD 2000 time is now 24 sec\n",
      "working on HD 2500 time is now 29 sec\n",
      "working on HD 3000 time is now 34 sec\n",
      "working on HD 3500 time is now 41 sec\n",
      "working on HD 4000 time is now 46 sec\n",
      "working on HD 4500 time is now 50 sec\n",
      "working on HD 5002 time is now 53 sec\n",
      "working on HD 5502 time is now 58 sec\n",
      "working on HD 6002 time is now 62 sec\n",
      "working on HD 6502 time is now 66 sec\n",
      "working on HD 7002 time is now 71 sec\n",
      "working on HD 7502 time is now 76 sec\n",
      "working on HD 8002 time is now 80 sec\n",
      "working on HD 8502 time is now 86 sec\n",
      "working on HD 9002 time is now 94 sec\n",
      "working on HD 9502 time is now 101 sec\n",
      "working on HD 10002 time is now 107 sec\n",
      "out of 10082 total HDs, there were 10082 0 0 0 HDs that were clean, discontig only, enclave-only, both problems after triage\n",
      "this took 107 seconds with maxLoop =  5\n"
     ]
    }
   ],
   "source": [
    "print(\"(not-so-)final check -- any more disco's ?\")\n",
    "maxLOOP = 5  #can increase to avoid false enclave detection\n",
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%500 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime),\"sec\")\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs, maxLOOP)\n",
    "    if not noEnclave:\n",
    "        noEnclave, enclaveList = isContiguous(list({u for u in range(nUnits)}.difference(set(HDunitList[t]))),unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems after triage\")\n",
    "print(\"this took\",int(time.time() - startTime),\"seconds with maxLoop = \", maxLOOP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "b78199da-ac7c-4cfb-ac0b-26363a8a8c56",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "defining and displaying current unit use after most recent manipulations; compare to original farther above.\n",
      "current avg use and its sd are 1.00582 0.10075\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#print(\"prev avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "print(\"defining and displaying current unit use after most recent manipulations; compare to original farther above.\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "de4d8af8-cc64-4215-9b95-f4c6a2bd03af",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "savedAgainUnitList = [HDunitList[t].copy() for t in range(nHDs)] #safekeeping    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "f4bb76c7-0ae0-40cb-9c6a-ee436dfc30c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "HDunitList = [savedAgainUnitList[t].copy() for t in range(nHDs)]  #restart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "f3bcd6a8-40b6-4764-a0d1-6814e3286cb8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking on our corner clusters and unit county usage\n",
      "usage, unit no, unit pop, type (0.5 = unit county, 0.25 = cluster) ...\n",
      "1.12437     0     6244 0.5\n",
      "0.91705     1     4437 0.5\n",
      "1.10751     2     13042 0.5\n",
      "1.01757     3     13288 0.5\n",
      "0.98629     4     10450 0.5\n",
      "0.96069     5     6245 0.5\n",
      "1.11251     6     13534 0.5\n",
      "1.06889     7     11985 0.5\n",
      "0.84769     8     7993 0.5\n",
      "0.9428     9     6387 0.5\n",
      "0.97328     10     9287 0.5\n",
      "1.13137     11     11742 0.5\n",
      "1.07572     12     13086 0.5\n",
      "1.00226     13     12297 0.5\n",
      "1.05335     14     14526 0.5\n",
      "0.97151     15     14739 0.5\n",
      "1.19724     16     5637 0.5\n",
      "1.15876     17     6902 0.5\n",
      "1.07891     18     4949 0.5\n",
      "1.05085     19     5400 0.5\n",
      "0.97953     20     11361 0.5\n",
      "1.22653     21     13761 0.5\n",
      "0.88326     22     13877 0.5\n",
      "0.97942     9675     211407 0.25\n",
      "1.02596     9676     82367 0.25\n",
      "1.10882     9677     83357 0.25\n"
     ]
    }
   ],
   "source": [
    "print(\"checking on our corner clusters and unit county usage\")\n",
    "print(\"usage, unit no, unit pop, type (0.5 = unit county, 0.25 = cluster) ...\")\n",
    "for u in range(nUnits):\n",
    "    if int(allUnits[u]) != allUnits[u] :\n",
    "        print(r5(unitUse[u]),\"   \",u,\"   \",int(unitPop[u]), allUnits[u]%1 )\n",
    "# note for MN, option 3 here led to tight CCB unit usage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "1e983c03-777a-4e81-bed0-34a620175f83",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "let's visualize over-used and underused units, < 0.75 or > 1.25\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and here is the histogram of HD pops relative to aDP\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "minUnitUse, maxUnitUse = 0.75, 1.25\n",
    "print(\"let's visualize over-used and underused units, <\",minUnitUse,\"or >\",maxUnitUse)\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < minUnitUse:\n",
    "        plotPoly(unitGeom[u],0.2)\n",
    "        plotCenter(\"u\",unitCP[u])\n",
    "    if unitUse[u] > maxUnitUse:\n",
    "        plotPoly(unitGeom[u], 1.5)\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()\n",
    "print(\"and here is the histogram of HD pops relative to aDP\")\n",
    "plt.hist([HDvPop[t]/aDP for t in popHDlist],bins = [0.4, 0.6, 0.7, 0.85, 0.9, 0.95,\n",
    "         0.98, 1.0, 1.02, 1.05, 1.1, 1.15, 1.3, 1.5, 2.0])\n",
    "plt.axvline(1.0,ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "9bc31b5a-992d-4a38-b9fe-3470b55e1e2e",
   "metadata": {},
   "outputs": [],
   "source": [
    "HDvPop = [0. for t in range(nHDs)]\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"opt3ContigButOffPop.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f6150cac-2249-415b-a364-edf55dc441ea",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "114705bb-9640-45f1-9f25-030030efaa63",
   "metadata": {},
   "outputs": [],
   "source": [
    "#below here -- working on tightening use distro while squaring up pop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "5d7d8519-eb3d-4345-9ac6-ab888e61c348",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "before patching, make another copy of the current HD lists\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pre-patch avg use and its sd are 1.00582 0.10075\n"
     ]
    }
   ],
   "source": [
    "print(\"before patching, make another copy of the current HD lists\")\n",
    "latestHDlist = [HDunitList[t].copy() for t in range(nHDs)]   #More safekeeping\n",
    "latestHDpop, latestUnitUse = [0. for t in range(nHDs)], [0. for u in range(nUnits)]\n",
    "for t in popHDlist:\n",
    "    for u in latestHDlist[t]:\n",
    "        latestHDpop[t] += unitPop[u]\n",
    "        latestUnitUse[u] += nDistricts * HDweight[t]\n",
    "latestUnitWeights, latestUnitDistro = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if latestUnitUse[u] > 0.1:\n",
    "        latestUnitDistro.append(latestUnitUse[u])\n",
    "        latestUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(latestUnitDistro, weights=latestUnitWeights, bins = 20, histtype = \"step\")\n",
    "plt.show()\n",
    "latestAvg, latestSD = getWeightedAvgAndSD(latestUnitDistro, latestUnitWeights)\n",
    "print(\"pre-patch avg use and its sd are\",r5(latestAvg),r5(latestSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "b1971853-bda7-49a4-9f25-1bdfd5e75aa2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on avg unit-to-HDcp dist for HD 0\n",
      "working on avg unit-to-HDcp dist for HD 800\n",
      "working on avg unit-to-HDcp dist for HD 1600\n",
      "working on avg unit-to-HDcp dist for HD 2400\n",
      "working on avg unit-to-HDcp dist for HD 3200\n",
      "working on avg unit-to-HDcp dist for HD 4000\n",
      "working on avg unit-to-HDcp dist for HD 4800\n",
      "working on avg unit-to-HDcp dist for HD 5602\n",
      "working on avg unit-to-HDcp dist for HD 6402\n",
      "working on avg unit-to-HDcp dist for HD 7202\n",
      "working on avg unit-to-HDcp dist for HD 8002\n",
      "working on avg unit-to-HDcp dist for HD 8802\n",
      "working on avg unit-to-HDcp dist for HD 9602\n"
     ]
    }
   ],
   "source": [
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%800 == 0:\n",
    "        print(\"working on avg unit-to-HDcp dist for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "f5b99900-614a-47df-b7de-5d59fffd6d3a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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AACx0w58D09TUpLq6Oo0aNUpdunRRUVGRM1ZeXq7Kykr5/X5Jkt/v14EDB1RdXe3MKSwslMfjUXJysjPn0n00z2neBwAAQIvuwCxcuFDjx49XQkKCzpw5o/Xr12v79u0qKCiQ1+vV9OnTlZOTo969e8vj8ejJJ5+U3+/XmDFjJEnjxo1TcnKypkyZouXLlysQCGjRokXKyspy7p7MnDlTr7zyiubNm6dp06Zp27Zt2rhxo/Ly+BtaAQDAn7UoYKqrq/XYY4/p5MmT8nq9Gj58uAoKCvTXf/3XkqQVK1YoPDxcGRkZqqurU1pamlavXu08PyIiQlu2bNGsWbPk9/vVvXt3TZ06Vc8995wzJzExUXl5eZozZ45WrlypAQMG6NVXX1VaWlorHTIAALDdDX8OTEfF58AAsBGfA4Ovujb/HBgAAID2QsAAAADrEDAAAMA6BAwAALAOAQMAAKxDwAAAAOsQMAAAwDoEDAAAsA4BAwAArEPAAAAA6xAwAADAOgQMAACwDgEDAACsQ8AAAADrEDAAAMA6BAwAALAOAQMAAKxDwAAAAOsQMAAAwDoEDAAAsA4BAwAArEPAAAAA6xAwAADAOgQMAACwDgEDAACsQ8AAAADrEDAAAMA6BAwAALAOAQMAAKxDwAAAAOsQMAAAwDoEDAAAsA4BAwAArEPAAAAA6xAwAADAOgQMAACwDgEDAACsQ8AAAADrEDAAAMA6BAwAALAOAQMAAKxDwAAAAOsQMAAAwDoEDAAAsA4BAwAArEPAAAAA6xAwAADAOgQMAACwDgEDAACsQ8AAAADrEDAAAMA6BAwAALAOAQMAAKxDwAAAAOsQMAAAwDotCpilS5fq61//unr27KmYmBh961vfUnl5ecicCxcuKCsrS3369FGPHj2UkZGhqqqqkDmVlZVKT09Xt27dFBMTo7lz5+rixYshc7Zv366RI0fK7XZr8ODBys3Nvb4jBAAAnU6LAqa4uFhZWVnavXu3CgsL1dDQoHHjxuncuXPOnDlz5mjz5s3atGmTiouLdeLECU2YMMEZb2xsVHp6uurr67Vr1y6tW7dOubm5Wrx4sTOnoqJC6enpGjt2rMrKypSdna0ZM2aooKCgFQ4ZAADYLswYY673yadOnVJMTIyKi4v1wAMPqLa2Vv369dP69ev16KOPSpKOHDmiIUOGqKSkRGPGjNHWrVv18MMP68SJE4qNjZUkrV27VvPnz9epU6fkcrk0f/585eXl6eDBg873mjRpkmpqapSfn39NawsGg/J6vaqtrZXH47neQwSAm+rWBXmtsp9Pl6W3yn6Am+1af37f0GtgamtrJUm9e/eWJJWWlqqhoUGpqanOnKSkJCUkJKikpESSVFJSomHDhjnxIklpaWkKBoM6dOiQM+fSfTTPad7HldTV1SkYDIY8AABA53TdAdPU1KTs7Gx94xvf0J133ilJCgQCcrlcio6ODpkbGxurQCDgzLk0XprHm8e+bE4wGNT58+evuJ6lS5fK6/U6j/j4+Os9NAAA0MFdd8BkZWXp4MGD2rBhQ2uu57otXLhQtbW1zuP48ePtvSQAANBGIq/nSbNnz9aWLVu0Y8cODRgwwNnu8/lUX1+vmpqakLswVVVV8vl8zpy9e/eG7K/5XUqXzvnLdy5VVVXJ4/EoKirqimtyu91yu93XczgAAMAyLboDY4zR7Nmz9fbbb2vbtm1KTEwMGR81apS6dOmioqIiZ1t5ebkqKyvl9/slSX6/XwcOHFB1dbUzp7CwUB6PR8nJyc6cS/fRPKd5HwAA4KutRXdgsrKytH79ev3qV79Sz549ndeseL1eRUVFyev1avr06crJyVHv3r3l8Xj05JNPyu/3a8yYMZKkcePGKTk5WVOmTNHy5csVCAS0aNEiZWVlOXdQZs6cqVdeeUXz5s3TtGnTtG3bNm3cuFF5ea3z6nwAAGC3Ft2BWbNmjWpra/VXf/VX6t+/v/N46623nDkrVqzQww8/rIyMDD3wwAPy+Xz65S9/6YxHRERoy5YtioiIkN/v13e/+1099thjeu6555w5iYmJysvLU2FhoUaMGKEXX3xRr776qtLS0lrhkAEAgO1u6HNgOjI+BwaAjfgcGHzV3ZTPgQEAAGgPBAwAALAOAQMAAKxDwAAAAOsQMAAAwDoEDAAAsA4BAwAArEPAAAAA6xAwAADAOgQMAACwDgEDAACsQ8AAAADrEDAAAMA6BAwAALAOAQMAAKxDwAAAAOsQMAAAwDoEDAAAsA4BAwAArEPAAAAA6xAwAADAOgQMAACwDgEDAACsQ8AAAADrEDAAAMA6BAwAALAOAQMAAKxDwAAAAOsQMAAAwDoEDAAAsA4BAwAArEPAAAAA6xAwAADAOgQMAACwDgEDAACsQ8AAAADrEDAAAMA6BAwAALAOAQMAAKxDwAAAAOsQMAAAwDoEDAAAsA4BAwAArEPAAAAA6xAwAADAOgQMAACwDgEDAACsQ8AAAADrEDAAAMA6BAwAALAOAQMAAKxDwAAAAOsQMAAAwDoEDAAAsA4BAwAArNPigNmxY4f+9m//VnFxcQoLC9M777wTMm6M0eLFi9W/f39FRUUpNTVVR48eDZlz+vRpZWZmyuPxKDo6WtOnT9fZs2dD5nz00Ue6//771bVrV8XHx2v58uUtPzoAANAptThgzp07pxEjRmjVqlVXHF++fLleeuklrV27Vnv27FH37t2VlpamCxcuOHMyMzN16NAhFRYWasuWLdqxY4eeeOIJZzwYDGrcuHEaOHCgSktL9cILL+jZZ5/Vz372s+s4RAAA0NmEGWPMdT85LExvv/22vvWtb0n6892XuLg4Pf300/rBD34gSaqtrVVsbKxyc3M1adIkffzxx0pOTta+ffs0evRoSVJ+fr7+5m/+Rp999pni4uK0Zs0aPfPMMwoEAnK5XJKkBQsW6J133tGRI0euaW3BYFBer1e1tbXyeDzXe4gAcFPduiCvVfbz6bL0VtkPcLNd68/vVn0NTEVFhQKBgFJTU51tXq9XKSkpKikpkSSVlJQoOjraiRdJSk1NVXh4uPbs2ePMeeCBB5x4kaS0tDSVl5fr888/v+L3rqurUzAYDHkAAIDOqVUDJhAISJJiY2NDtsfGxjpjgUBAMTExIeORkZHq3bt3yJwr7ePS7/GXli5dKq/X6zzi4+Nv/IAAAECH1GnehbRw4ULV1tY6j+PHj7f3kgAAQBtp1YDx+XySpKqqqpDtVVVVzpjP51N1dXXI+MWLF3X69OmQOVfax6Xf4y+53W55PJ6QBwAA6JxaNWASExPl8/lUVFTkbAsGg9qzZ4/8fr8kye/3q6amRqWlpc6cbdu2qampSSkpKc6cHTt2qKGhwZlTWFioO+64Q7169WrNJQMAAAu1OGDOnj2rsrIylZWVSfrzC3fLyspUWVmpsLAwZWdn61/+5V/061//WgcOHNBjjz2muLg4551KQ4YM0Te/+U19//vf1969e/XBBx9o9uzZmjRpkuLi4iRJ//AP/yCXy6Xp06fr0KFDeuutt7Ry5Url5OS02oEDAAB7Rbb0Cfv379fYsWOdr5ujYurUqcrNzdW8efN07tw5PfHEE6qpqdF9992n/Px8de3a1XnOm2++qdmzZ+uhhx5SeHi4MjIy9NJLLznjXq9X7733nrKysjRq1Cj17dtXixcvDvmsGAAA8NV1Q58D05HxOTAAbMTnwOCrrl0+BwYAAOBmIGAAAIB1CBgAAGAdAgYAAFiHgAEAANYhYAAAgHUIGAAAYB0CBgAAWIeAAQAA1iFgAACAdQgYAABgHQIGAABYh4ABAADWIWAAAIB1CBgAAGAdAgYAAFiHgAEAANYhYAAAgHUIGAAAYB0CBgAAWIeAAQAA1iFgAACAdQgYAABgHQIGAABYh4ABAADWIWAAAIB1CBgAAGAdAgYAAFiHgAEAANYhYAAAgHUIGAAAYB0CBgAAWIeAAQAA1iFgAACAdQgYAABgHQIGAABYh4ABAADWIWAAAIB1CBgAAGAdAgYAAFiHgAEAANYhYAAAgHUIGAAAYB0CBgAAWIeAAQAA1iFgAACAdQgYAABgncj2XgAAoPXduiDvqnM+XZZ+E1YCtA3uwAAAAOsQMAAAwDr8CgkAbpJr+bUObhy/Pvtq4A4MAACwDndgAKAVcHfl5uA8oxkBAwBfUa0VA/w6Bu2BgAGAq+D/+oGOp0MHzKpVq/TCCy8oEAhoxIgRevnll3XPPfe097IAdCLEyY3jTg7aQ4cNmLfeeks5OTlau3atUlJS9JOf/ERpaWkqLy9XTExMey8PANDKbmZM2vhOJRvX3JbCjDGmvRdxJSkpKfr617+uV155RZLU1NSk+Ph4Pfnkk1qwYMFVnx8MBuX1elVbWyuPx9PWywVwjTraf4S5A4Mb0VrXake7DtszhK7153eHvANTX1+v0tJSLVy40NkWHh6u1NRUlZSUXPE5dXV1qqurc76ura2V9OcTAeDmuHNJQavs51r+vW2t7wXciIQ5m9p7CW2iPX92Nn/vq91f6ZAB84c//EGNjY2KjY0N2R4bG6sjR45c8TlLly7Vj370o8u2x8fHt8kaAbQd70/aewXAV1tH+HfwzJkz8nq9XzjeIQPmeixcuFA5OTnO101NTTp9+rT69OmjsLCwdlxZxxYMBhUfH6/jx4/zq7abhHN+83HO2wfn/ebrDOfcGKMzZ84oLi7uS+d1yIDp27evIiIiVFVVFbK9qqpKPp/vis9xu91yu90h26Kjo9tqiZ2Ox+Ox9mK3Fef85uOctw/O+81n+zn/sjsvzTrkXyXgcrk0atQoFRUVOduamppUVFQkv9/fjisDAAAdQYe8AyNJOTk5mjp1qkaPHq177rlHP/nJT3Tu3Dk9/vjj7b00AADQzjpswEycOFGnTp3S4sWLFQgEdNdddyk/P/+yF/bixrjdbi1ZsuSyX7+h7XDObz7OefvgvN98X6Vz3mE/BwYAAOCLdMjXwAAAAHwZAgYAAFiHgAEAANYhYAAAgHUImA7u2WefVVhYWMgjKSnJGb9w4YKysrLUp08f9ejRQxkZGZd9AGBlZaXS09PVrVs3xcTEaO7cubp48WLInO3bt2vkyJFyu90aPHiwcnNzL1vLqlWrdOutt6pr165KSUnR3r17Q8avZS22+P3vf6/vfve76tOnj6KiojRs2DDt37/fGTfGaPHixerfv7+ioqKUmpqqo0ePhuzj9OnTyszMlMfjUXR0tKZPn66zZ8+GzPnoo490//33q2vXroqPj9fy5csvW8umTZuUlJSkrl27atiwYXr33XdDxq9lLR3drbfeetl1HhYWpqysLElc522lsbFRP/zhD5WYmKioqCjddtttev7550P+Dhqu9dZ35swZZWdna+DAgYqKitK9996rffv2OeOc82tk0KEtWbLEDB061Jw8edJ5nDp1yhmfOXOmiY+PN0VFRWb//v1mzJgx5t5773XGL168aO68806Tmppq/ud//se8++67pm/fvmbhwoXOnGPHjplu3bqZnJwcc/jwYfPyyy+biIgIk5+f78zZsGGDcblc5j/+4z/MoUOHzPe//30THR1tqqqqrnkttjh9+rQZOHCg+d73vmf27Nljjh07ZgoKCswnn3zizFm2bJnxer3mnXfeMR9++KH5u7/7O5OYmGjOnz/vzPnmN79pRowYYXbv3m3+67/+ywwePNhMnjzZGa+trTWxsbEmMzPTHDx40PziF78wUVFR5qc//akz54MPPjARERFm+fLl5vDhw2bRokWmS5cu5sCBAy1aS0dXXV0dco0XFhYaSeb99983xnCdt5Uf//jHpk+fPmbLli2moqLCbNq0yfTo0cOsXLnSmcO13vq+853vmOTkZFNcXGyOHj1qlixZYjwej/nss8+MMZzza0XAdHBLliwxI0aMuOJYTU2N6dKli9m0aZOz7eOPPzaSTElJiTHGmHfffdeEh4ebQCDgzFmzZo3xeDymrq7OGGPMvHnzzNChQ0P2PXHiRJOWluZ8fc8995isrCzn68bGRhMXF2eWLl16zWuxxfz588199933heNNTU3G5/OZF154wdlWU1Nj3G63+cUvfmGMMebw4cNGktm3b58zZ+vWrSYsLMz8/ve/N8YYs3r1atOrVy/nz6H5e99xxx3O19/5zndMenp6yPdPSUkx//iP/3jNa7HRU089ZW677TbT1NTEdd6G0tPTzbRp00K2TZgwwWRmZhpjuNbbwp/+9CcTERFhtmzZErJ95MiR5plnnuGctwC/QrLA0aNHFRcXp0GDBikzM1OVlZWSpNLSUjU0NCg1NdWZm5SUpISEBJWUlEiSSkpKNGzYsJAPAExLS1MwGNShQ4ecOZfuo3lO8z7q6+tVWloaMic8PFypqanOnGtZiy1+/etfa/To0fr7v/97xcTE6O6779bPf/5zZ7yiokKBQCDkWL1er1JSUkLOe3R0tEaPHu3MSU1NVXh4uPbs2ePMeeCBB+RyuZw5aWlpKi8v1+eff+7M+bI/m2tZi23q6+v1xhtvaNq0aQoLC+M6b0P33nuvioqK9Nvf/laS9OGHH2rnzp0aP368JK71tnDx4kU1Njaqa9euIdujoqK0c+dOznkLEDAdXEpKinJzc5Wfn681a9aooqJC999/v86cOaNAICCXy3XZX1oZGxurQCAgSQoEApd9enHz11ebEwwGdf78ef3hD39QY2PjFedcuo+rrcUWx44d05o1a/S1r31NBQUFmjVrlv75n/9Z69atk/T/5+1q5yMmJiZkPDIyUr17926VP5tLx6+2Ftu88847qqmp0fe+9z1J13ZtcZ1fnwULFmjSpElKSkpSly5ddPfddys7O1uZmZmSuNbbQs+ePeX3+/X888/rxIkTamxs1BtvvKGSkhKdPHmSc94CHfavEsCfNf+fkCQNHz5cKSkpGjhwoDZu3KioqKh2XFnn1dTUpNGjR+tf//VfJUl33323Dh48qLVr12rq1KntvLrO77XXXtP48eMVFxfX3kvp9DZu3Kg333xT69ev19ChQ1VWVqbs7GzFxcVxrbeh//zP/9S0adN0yy23KCIiQiNHjtTkyZNVWlra3kuzCndgLBMdHa3bb79dn3zyiXw+n+rr61VTUxMyp6qqSj6fT5Lk8/kue4dE89dXm+PxeBQVFaW+ffsqIiLiinMu3cfV1mKL/v37Kzk5OWTbkCFDnF/dNR/P1c5HdXV1yPjFixd1+vTpVvmzuXT8amuxyf/+7//qN7/5jWbMmOFs4zpvO3PnznXuwgwbNkxTpkzRnDlztHTpUklc623ltttuU3Fxsc6ePavjx49r7969amho0KBBgzjnLUDAWObs2bP63e9+p/79+2vUqFHq0qWLioqKnPHy8nJVVlbK7/dLkvx+vw4cOBBysRcWFsrj8Tg/pP1+f8g+muc078PlcmnUqFEhc5qamlRUVOTMuZa12OIb3/iGysvLQ7b99re/1cCBAyVJiYmJ8vl8IccaDAa1Z8+ekPNeU1MT8n9U27ZtU1NTk1JSUpw5O3bsUENDgzOnsLBQd9xxh3r16uXM+bI/m2tZi01ef/11xcTEKD093dnGdd52/vSnPyk8PPTHQEREhJqamiRxrbe17t27q3///vr8889VUFCgRx55hHPeEu39KmJ8uaefftps377dVFRUmA8++MCkpqaavn37murqamPMn9/SmZCQYLZt22b2799v/H6/8fv9zvOb3146btw4U1ZWZvLz802/fv2u+PbSuXPnmo8//tisWrXqim8vdbvdJjc31xw+fNg88cQTJjo6OuRdH1dbiy327t1rIiMjzY9//GNz9OhR8+abb5pu3bqZN954w5mzbNkyEx0dbX71q1+Zjz76yDzyyCNXfJvj3Xffbfbs2WN27txpvva1r4W8zbGmpsbExsaaKVOmmIMHD5oNGzaYbt26XfY2x8jISPNv//Zv5uOPPzZLliy54tscr7YWGzQ2NpqEhAQzf/78y8a4ztvG1KlTzS233OK8jfqXv/yl6du3r5k3b54zh2u99eXn55utW7eaY8eOmffee8+MGDHCpKSkmPr6emMM5/xaETAd3MSJE03//v2Ny+Uyt9xyi5k4cWLI55GcP3/e/NM//ZPp1auX6datm/n2t79tTp48GbKPTz/91IwfP95ERUWZvn37mqeffto0NDSEzHn//ffNXXfdZVwulxk0aJB5/fXXL1vLyy+/bBISEozL5TL33HOP2b17d8j4tazFFps3bzZ33nmncbvdJikpyfzsZz8LGW9qajI//OEPTWxsrHG73eahhx4y5eXlIXP++Mc/msmTJ5sePXoYj8djHn/8cXPmzJmQOR9++KG57777jNvtNrfccotZtmzZZWvZuHGjuf32243L5TJDhw41eXl5LV6LDQoKCoykK66d67xtBINB89RTT5mEhATTtWtXM2jQIPPMM8+EvPWWa731vfXWW2bQoEHG5XIZn89nsrKyTE1NjTPOOb82YcZc8pGLAAAAFuA1MAAAwDoEDAAAsA4BAwAArEPAAAAA6xAwAADAOgQMAACwDgEDAACsQ8AAAADrEDAAAMA6BAwAALAOAQMAAKxDwAAAAOv8H0oa9m2VLwGRAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "before patching, make another copy of the current HD lists\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pre-patch avg use and its sd are 1.00582 0.10075\n"
     ]
    }
   ],
   "source": [
    "#Restart - may want to comment out first line\n",
    "HDunitList = [latestHDlist[t].copy() for t in range(nHDs)]\n",
    "unitUse = [0. for u in range(nUnits) ]\n",
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in range(nHDs) ]\n",
    "\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse, weights = unitPop,bins = 50)\n",
    "plt.show()\n",
    "plt.hist([HDvPop[t] for t in popHDlist], bins=50)\n",
    "plt.show()\n",
    "print(\"before patching, make another copy of the current HD lists\")\n",
    "latestHDlist = [HDunitList[t].copy() for t in range(nHDs)]   #More safekeeping\n",
    "latestHDpop, latestUnitUse = [0. for t in range(nHDs)], [0. for u in range(nUnits)]\n",
    "for u in range(nUnits):\n",
    "    if latestUnitUse[u] > 0.1:\n",
    "        latestUnitDistro.append(latestUnitUse[u])\n",
    "        latestUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(latestUnitDistro, weights=latestUnitWeights, bins = 20, histtype = \"step\")\n",
    "plt.show()\n",
    "latestAvg, latestSD = getWeightedAvgAndSD(latestUnitDistro, latestUnitWeights)\n",
    "print(\"pre-patch avg use and its sd are\",r5(latestAvg),r5(latestSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cea58fc2-c389-474a-9800-0f4906640a27",
   "metadata": {},
   "outputs": [],
   "source": [
    "#WA - OPTIONAL restart here, pull in file*********************\n",
    "print(\"this optional RESTART block pulls in an existing UNIT (not vtd) list for squaring up\") \n",
    "print(\"Must have already established unitGeoms, pops, topology in above blocks\")\n",
    "guessedFile = \"enter the unpatched UNIT list file, e.g. ./2024state_HD_output/\"+STATE+str(nHDs)+\"opt3ContigButOffPopUnit.csv\"\n",
    "infile = input(guessedFile)\n",
    "inDF = pd.read_csv(infile)\n",
    "vtdListString = inDF[\"HDunitList\"]  #inDF[\"HDvtdList\"]\n",
    "nHDs = len(vtdListString)\n",
    "inVTDlist = [ast.literal_eval(vtdListString[t]) for t in range(nHDs)]\n",
    "HDweight = inDF[\"HDweight\"]\n",
    "sumWt = np.sum(HDweight)\n",
    "print(\"sum of HDweight should be unity, actually is\",sumWt)\n",
    "print(\"I will now renormalize\")\n",
    "HDweight = [HDweight[t] /sumWt for t in range(nHDs)]\n",
    "print(\"normalized weight is now\",np.sum(HDweight))\n",
    "HDvPop = inDF[\"HDvPop\"].to_list()\n",
    "hdCPx, hdCPy = inDF[\"centroid x\"], inDF[\"centroid y\"]\n",
    "hdCP = [Point(hdCPx[t], hdCPy[t]) for t in range(nHDs)]\n",
    "print(\"I read in\",nHDs,\"HD lists of units\") #vtds\")\n",
    "HDunitList = [inVTDlist[t].copy() for t in range(nHDs)]\n",
    "unitUse = [0. for u in range(nUnits) ]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse,weights = unitPop)\n",
    "print(\"weighted unit use histogram\")\n",
    "plt.show()\n",
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "for t in range(nHDs):\n",
    "    if len(HDunitList[t]) > 0:\n",
    "        popHDlist.append(t)\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%800 == 0:\n",
    "        print(\"working on avg unit-to-HDcp dist for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "27b51cd0-8bb6-4b16-bb79-37498e59ce5c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will now square up the 615 HDs with pop < 746140 to within 1045\n",
      "working on squaring up HD 8 time is now 0\n",
      "working on squaring up HD 863 time is now 1155\n",
      "working on squaring up HD 1644 time is now 1410\n",
      "working on squaring up HD 2840 time is now 2652\n",
      "working on squaring up HD 4700 time is now 2722\n",
      "working on squaring up HD 8963 time is now 3049\n",
      "working on squaring up HD 10049 time is now 5177\n",
      "We have addressed underpop in a total of 615 HDs\n",
      "Here is a scatterplot of original (x) to final pop (y)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#SQUARING UP UNDERPOPPED\n",
    "HDnAddedUnits, HDaddedPop = [0]*nHDs, [0.]*nHDs\n",
    "underPoppedList = list()\n",
    "minDistrictPop, maxDistrictPop = 0.99 * aDP, 1.01 * aDP\n",
    "for t,pop in enumerate(HDvPop):\n",
    "    if pop < minDistrictPop and t in popHDlist:\n",
    "        underPoppedList.append(t)\n",
    "startTime = time.time()\n",
    "maxGap = 0.9 * np.median(unitPop)\n",
    "print(\"We will now square up the\",len(underPoppedList),\"HDs with pop <\",int(minDistrictPop),\"to within\",int(maxGap) ) \n",
    "for ii,t in enumerate(underPoppedList):\n",
    "    if ii%100 == 0:\n",
    "        print(\"working on squaring up HD\",t,\"time is now\",int(time.time() - startTime)) \n",
    "    gap = aDP - HDvPop[t]\n",
    "    origGap = gap\n",
    "    nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "    for u in HDunitList[t]:\n",
    "        for uu in unitNbrs[u]:\n",
    "            if uu not in HDunitList[t] and uu not in nearHDlist and unitPop[uu] < gap + maxGap:\n",
    "                nearHDlist.append(uu)   #below line: bias toward close, underused\n",
    "                nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  \n",
    "    currList = HDunitList[t].copy()\n",
    "    addedList = list()\n",
    "    stillGoing = True\n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)  #NOTE - HAVE NOT MOVED TO AVOIDEDENCLAVE HERE (YET)\n",
    "            if canAdd: \n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else:\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  #bias toward close, underused\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    HDunitList[t] += addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    HDnAddedUnits[t] = len(addedList)\n",
    "    HDaddedPop[t] = np.sum( [unitPop[u] for u in addedList] )\n",
    "    if HDvPop[t] > maxDistrictPop:\n",
    "        print(\"Oops! HD\",t,\"now has overshot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after adding\",HDaddedPop[t] )\n",
    "print(\"We have addressed underpop in a total of\",len(underPoppedList),\"HDs\")\n",
    "print(\"Here is a scatterplot of original (x) to final pop (y)\")\n",
    "plt.scatter([HDvPop[t] - HDaddedPop[t] for t in underPoppedList], [HDvPop[t] for t in underPoppedList])\n",
    "plt.axhline(y=aDP, xmin = 0.9*aDP, xmax = 1.1*aDP, ls=\"--\")\n",
    "plt.axvline(x=aDP, ymin = 0.9*aDP, ymax = 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "219aa49b-8618-4150-85ec-108762374258",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "intermediate save on slow state\n"
     ]
    }
   ],
   "source": [
    "print(\"intermediate save on slow state\")\n",
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"opt3ContigUnderPop.csv\" #\"contigUnpatchedB.csv\" unpatchedContigGoodPop.csv\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "bc01409d-d9e4-43a6-9fae-c76aa7bdc855",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "amped unit avg and sd usage are 1.0083 0.09947\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#prevUnitUse = [0.]*nUnits\n",
    "#for t in popHDlist:\n",
    "#    for u in latestHDlist[t]:\n",
    "#        prevUnitUse[u] += HDweight[t] * nDistricts\n",
    "\n",
    "ampedUnitUse = [0. for u in range(nUnits)]\n",
    "ampedHDlist = [HDunitList[t].copy() for t in range(nHDs)]\n",
    "ampedHDpop = [HDvPop[t] for t in range(nHDs) ]\n",
    "for t in popHDlist:\n",
    "    for u in ampedHDlist[t]:\n",
    "        ampedUnitUse[u] += HDweight[t] * nDistricts   #KISS - recalc these\n",
    "#plt.hist(prevUnitUse,bins=50,weights=unitPop,label=\"previous\",histtype=\"step\")\n",
    "plt.hist(ampedUnitUse, bins=50, weights=unitPop,label=\"amped\",histtype=\"step\")\n",
    "plt.legend()\n",
    "ampedUnitUseAvg, ampedUnitUseSD = getWeightedAvgAndSD(ampedUnitUse,unitPop)\n",
    "#print(\"previous unit avg and sd usage are\",r5(latestAvg), r5(latestSD) )\n",
    "print(\"amped unit avg and sd usage are\",r5(ampedUnitUseAvg), r5(ampedUnitUseSD) )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "ee512b2b-4daa-4a6b-9452-e8dfdfdebc88",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the current barredJettisonSet (usually CCB's) is {9675, 9676, 9677}\n",
      "9675 0.9794183152901953\n",
      "9676 1.0259568228172167\n",
      "9677 1.1128242807732984\n"
     ]
    }
   ],
   "source": [
    "#CHECK ON BARRED JETTISON SET BEFORE RUNNING BELOW\n",
    "barredJettisonSet = set()\n",
    "for u in range(nUnits):\n",
    "    if abs(allUnits[u] - int(allUnits[u]) - 0.25) < 0.01:\n",
    "        barredJettisonSet.add(u)\n",
    "print(\"the current barredJettisonSet (usually CCB's) is\",barredJettisonSet)\n",
    "for u in barredJettisonSet:\n",
    "    print(u,unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "5a6cb84c-1d0f-4f02-831c-985fe4078dc8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{9675, 9676} {9675, 9676, 9677}\n"
     ]
    }
   ],
   "source": [
    "origBarredJettisonSet = set(list(barredJettisonSet))\n",
    "for u in origBarredJettisonSet:\n",
    "    if unitUse[u] > 1.04:\n",
    "        barredJettisonSet.remove(u)  #this one is overused in this state\n",
    "print(barredJettisonSet, origBarredJettisonSet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "dd7d9818-344c-4150-917b-57a4ee051c92",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\n",
      "Let's now square down the 1202 overPopped HDs to within 1045\n",
      "working on squaring down HD 13 time is now 0\n",
      "working on squaring down HD 492 time is now 56\n",
      "working on squaring down HD 847 time is now 88\n",
      "working on squaring down HD 1010 time is now 93\n",
      "working on squaring down HD 1346 time is now 95\n",
      "working on squaring down HD 1901 time is now 100\n",
      "working on squaring down HD 2068 time is now 117\n",
      "working on squaring down HD 2191 time is now 122\n",
      "working on squaring down HD 2309 time is now 127\n",
      "working on squaring down HD 2526 time is now 164\n",
      "working on squaring down HD 2689 time is now 170\n",
      "working on squaring down HD 2976 time is now 182\n",
      "working on squaring down HD 3125 time is now 241\n",
      "working on squaring down HD 3330 time is now 435\n",
      "working on squaring down HD 3516 time is now 600\n",
      "working on squaring down HD 4541 time is now 681\n",
      "working on squaring down HD 7822 time is now 688\n",
      "working on squaring down HD 9387 time is now 776\n",
      "working on squaring down HD 9639 time is now 785\n",
      "working on squaring down HD 9785 time is now 811\n",
      "working on squaring down HD 10069 time is now 820\n",
      "We have addressed overpop in a total of 1202 HDs\n",
      "Here is a scatterplot of original to final pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#SQUARING DOWN  #the barred set is dynamic; we stop shedding upon underuse\n",
    "print(\"Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\")\n",
    "#HDunitList = [ampedHDlist[t].copy() for t in range(nHDs)]\n",
    "#HDvPop =     [ampedHDpop[t]         for t in range(nHDs)]\n",
    "#unitUse =    [ampedUnitUse[u]       for u in range(nUnits)] #saving in case I need to re-run\n",
    "HDnShedUnits = [0]*nHDs\n",
    "overPoppedList = list()\n",
    "startTime = time.time()\n",
    "for t,pop in enumerate(HDvPop):\n",
    "    if pop > maxDistrictPop and t in popHDlist:\n",
    "        overPoppedList.append(t)\n",
    "maxGap = 0.9 * np.median(unitPop)   \n",
    "print(\"Let's now square down the\",len(overPoppedList),\"overPopped HDs to within\", int(maxGap))  \n",
    "barredSet = set(list(barredJettisonSet))\n",
    "for ii,t in enumerate(overPoppedList):\n",
    "    for u in origBarredJettisonSet:\n",
    "        if unitUse[u] < 1.00:\n",
    "            barredSet = barredSet.union({u})  #adding back in when become underused \n",
    "    if ii%60 == 0:\n",
    "        print(\"working on squaring down HD\",t,\"time is now\",int(time.time()-startTime))\n",
    "    unbroken, noEnclave, sPL, ePL = enclaveCheck(HDunitList[t],unitNbrs)\n",
    "    if not (unbroken and noEnclave):\n",
    "        print(\"SKIPPING shedding attempt on overpopped HD\",t,\"with pop\",HDvPop[t],\"because it was not legal to start\")\n",
    "    else:\n",
    "        #avgDist = np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "        excess = HDvPop[t] - aDP\n",
    "        origExcess = excess\n",
    "        HDboundaryList, HDboundaryScore = list(), list()  #these will be dynamic lists of the overused border units to jettison\n",
    "        distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "        starterU = HDunitList[t][distList.index(np.min(distList))]\n",
    "        #barredSet = barredJettisonSet  #see above for VA-on modification\n",
    "        #barredSet = set(get2nbrs([starterU],unitNbrs)).union(barredJettisonSet)  #weaker specification - must be close to be barred\n",
    "\n",
    "        for u in set(HDunitList[t]).difference(barredSet):\n",
    "            isBoundary = False\n",
    "            for uu in unitNbrs[u]:\n",
    "                if uu not in HDunitList[t]:\n",
    "                    isBoundary = True\n",
    "                    break\n",
    "            if isBoundary and HDvPop[t] - unitPop[u] > aDP - maxGap:  #shedding this unit won't send us too far under targetpop\n",
    "                HDboundaryList.append(u)\n",
    "                HDboundaryScore.append((1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t])  #low-score = bias toward far, overused\n",
    "        currList = HDunitList[t].copy()\n",
    "        shedList, stillGoing = list(), True\n",
    "        while excess > maxGap and len(HDboundaryList) > 0 and stillGoing:   #shed the highest-scoring neighboring overused unit until we've roughly squared the HDpop\n",
    "            idx, i, notYetPicked = np.argsort(HDboundaryScore), 0, True\n",
    "            while i < len(HDboundaryScore) and notYetPicked and stillGoing:        \n",
    "                listNo = idx[i]   #low (large negative) score is preferred to shed\n",
    "                unitNoToShed = HDboundaryList[listNo]  # attempt to shed this unit ...\n",
    "                tryList = list(set(currList).difference( {unitNoToShed} ) )\n",
    "                contig = avoidedIsland(tryList, unitNbrs, [unitNoToShed] )  #new for MO - faster contig check\n",
    "                #unbroken, noEnclave, sPL, ePL = enclaveCheck(tryList,unitNbrs) \n",
    "                #if unbroken and noEnclave:             #... if that won't eff up contiguity\n",
    "                if contig:\n",
    "                    notYetPicked = False\n",
    "                else:\n",
    "                    i +=1\n",
    "            if notYetPicked:\n",
    "                stillGoing = False  #can't drop any more units without creating an enclave\n",
    "                print(\"can't drop any more units to HD\",t,\"without creating an enclave\")\n",
    "            else: #add this eligible unit\n",
    "                shedList.append(unitNoToShed)\n",
    "                excess -= unitPop[unitNoToShed]        \n",
    "                del currList[currList.index(unitNoToShed) ]\n",
    "                del HDboundaryList[listNo]\n",
    "                del HDboundaryScore[listNo]\n",
    "                for u in unitNbrs[unitNoToShed]:      # ... and ID any neighboring units that will now be on boundary after we shed this unit\n",
    "                    if u in currList and u not in HDboundaryList and (unitPop[u] <= excess + maxGap and\n",
    "                                                                      u not in barredSet): \n",
    "                        HDboundaryList.append(u)\n",
    "                        HDboundaryScore.append( (1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t] )  #low-score, bias toward far & overused       \n",
    "                for uu in HDboundaryList.copy():\n",
    "                    if unitPop[uu] > excess + maxGap:  #checking to see if the latest pop change DQ's any large units on current boundary\n",
    "                        del HDboundaryScore[HDboundaryList.index(uu)]\n",
    "                        del HDboundaryList[HDboundaryList.index(uu)]   \n",
    "        for u in shedList:\n",
    "            unitUse[u] -= HDweight[t] * nDistricts\n",
    "        HDunitList[t], HDvPop[t] = currList.copy(), np.sum( [unitPop[u] for u in currList ] )    \n",
    "        if HDvPop[t] < minDistrictPop:\n",
    "            print(\"Oops! HD\",t,\"now has undershot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after shedding\",\n",
    "                 np.sum([unitPop[u] for u in shedList]) )\n",
    "\n",
    "        HDnShedUnits[t] = -1 * len(shedList)\n",
    "\n",
    "print(\"We have addressed overpop in a total of\",len(overPoppedList),\"HDs\")\n",
    "print(\"Here is a scatterplot of original to final pop\")\n",
    "plt.scatter([ampedHDpop[t] for t in overPoppedList], [HDvPop[t] for t in overPoppedList])\n",
    "plt.axhline(aDP, 0.9*aDP, 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5c4c929d-0208-4785-aa15-5681a493a530",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "9a19b23e-43cc-4609-9ee7-6d1057a7a9e1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here are the stats prior to any equi-pop patching\n",
      "amped unit avg and sd usage are 1.0083 0.09947\n",
      "shed unit avg and sd usage are 1.00101 0.09408\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and here are the final populations\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 10084\n",
      "working on HD 600 out of 10084\n",
      "working on HD 1200 out of 10084\n",
      "working on HD 1800 out of 10084\n",
      "working on HD 2400 out of 10084\n",
      "working on HD 3000 out of 10084\n",
      "working on HD 3600 out of 10084\n",
      "working on HD 4200 out of 10084\n",
      "working on HD 4800 out of 10084\n",
      "working on HD 5402 out of 10084\n",
      "working on HD 6002 out of 10084\n",
      "working on HD 6602 out of 10084\n",
      "working on HD 7202 out of 10084\n",
      "working on HD 7802 out of 10084\n",
      "working on HD 8402 out of 10084\n",
      "working on HD 9002 out of 10084\n",
      "working on HD 9602 out of 10084\n",
      "all done checking HD and complement contiguity for all 10084 HDs\n",
      "underpop contigFail, enclaveFail = 0 0 out of 615\n",
      "overpop contigFail, enclaveFail = 0 0 out of 1202\n",
      "total contigFail, enclaveFail =  0 0\n",
      "CCB unit 9675 with pop 211407.0 now has use 0.97942\n",
      "CCB unit 9676 with pop 82367.0 now has use 1.02596\n",
      "CCB unit 9677 with pop 83357.0 now has use 0.99889\n"
     ]
    }
   ],
   "source": [
    "print(\"Here are the stats prior to any equi-pop patching\")\n",
    "shedUnitUse = [0. for u in range(nUnits)]\n",
    "shedHDlist = [HDunitList[t].copy() for t in range(nHDs)]\n",
    "shedHDpop = [HDvPop[t] for t in range(nHDs) ]\n",
    "for t in popHDlist:\n",
    "    for u in shedHDlist[t]:\n",
    "        shedUnitUse[u] += HDweight[t] * nDistricts   #KISS - recalc these\n",
    "#plt.hist(latestUnitUse,bins=50,weights=unitPop,label=\"pre-squaring\",histtype=\"step\")\n",
    "plt.hist(ampedUnitUse, bins=50, weights=unitPop,label=\"amped\",histtype=\"step\")\n",
    "plt.hist(shedUnitUse, bins=50, weights=unitPop,label=\"shed\",histtype=\"step\")\n",
    "plt.legend()\n",
    "#latestAvg, latestSD = getWeightedAvgAndSD(latestUnitUse,unitPop)\n",
    "shedUnitUseAvg, shedUnitUseSD = getWeightedAvgAndSD(shedUnitUse,unitPop)\n",
    "#print(\"orig unit avg and sd usage are\",r5(latestAvg), r5(latestSD) )\n",
    "print(\"amped unit avg and sd usage are\",r5(ampedUnitUseAvg), r5(ampedUnitUseSD) )\n",
    "print(\"shed unit avg and sd usage are\", r5(shedUnitUseAvg),  r5(shedUnitUseSD) )\n",
    "plt.show()\n",
    "# note: when I ran this early Jan, went from 0.12662 to 0.09961 to 0.09432 SD orig-amped-shed, but contig not yet done\n",
    "print(\"and here are the final populations\")\n",
    "plt.hist([shedHDpop[t] for t in popHDlist],bins=20)\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "failEnclaveSet, failContigSet = set(), set()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%600 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs,5)\n",
    "    if not noEnclave:\n",
    "        noEnclave, eList = isContiguous(list({u for u in range(nUnits)}.difference(set(HDunitList[t]))),unitNbrs)\n",
    "    if not unbroken or not noEnclave:\n",
    "        #print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "        pass\n",
    "    if not unbroken:\n",
    "        failContigSet.add(t)\n",
    "    if not noEnclave:\n",
    "        failEnclaveSet.add(t)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")\n",
    "failContigUnderpopped, failEnclaveUnderpopped = set(underPoppedList).intersection(failContigSet), set(underPoppedList).intersection(failEnclaveSet)\n",
    "failContigOverpopped, failEnclaveOverpopped = set(overPoppedList).intersection(failContigSet), set(overPoppedList).intersection(failEnclaveSet)\n",
    "print(\"underpop contigFail, enclaveFail =\",len(failContigUnderpopped), len(failEnclaveUnderpopped),\"out of\",len(underPoppedList))\n",
    "print(\"overpop contigFail, enclaveFail =\",len(failContigOverpopped), len(failEnclaveOverpopped),\"out of\",len(overPoppedList))\n",
    "print(\"total contigFail, enclaveFail = \",len(failContigSet), len(failEnclaveSet) )\n",
    "for u in range(nUnits):\n",
    "    if abs( allUnits[u]%1 - 0.25) < 0.01:\n",
    "        print(\"CCB unit\",u,\"with pop\",unitPop[u],\"now has use\",r5(unitUse[u]) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "ff3288f1-f9ca-473c-886c-ee8d6c2637bf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10084 9678\n"
     ]
    }
   ],
   "source": [
    "print(nHDs, nUnits)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1ed668f8-bf1e-46eb-963f-cf5e2b935b11",
   "metadata": {},
   "outputs": [],
   "source": [
    "#see MD code if we need to remove a stuck CCB's from any HDs and then redo the square-up after dropping them"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "e7bfa674-8fc8-42c8-86e9-76d334d3c47c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"opt3ContigGoodPop.csv\" #\"contigUnpatchedB.csv\" unpatchedContigGoodPop.csv\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 430,
   "id": "c0c3a3d8-cf79-40ad-aa2e-b6793266f1d4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "prior to patching, write these contiguous lists to a file, converting to vtd lists\n"
     ]
    }
   ],
   "source": [
    "#SKIP THIS FOR STATES WITH FRAGMENTED VTD'S ###########\n",
    "print(\"prior to patching, write these contiguous lists to a file, converting to vtd lists\")\n",
    "tList = [t for t in range(nHDs)]\n",
    "vtdList = [list() for t in range(nHDs)]\n",
    "unitVTDlist = [list() for u in range(nUnits)]\n",
    "for u in range(nUnits):\n",
    "    if allUnits[u] % 1 == 0.5 :\n",
    "        c = int(allUnits[u])\n",
    "        unitVTDlist[u] = countyTractList[c].copy()\n",
    "    if allUnits[u] % 1 == 0.25 :\n",
    "        CCBnumber = int(allUnits[u])\n",
    "        for c in CCBlist[CCBnumber] :\n",
    "            unitVTDlist[u] += countyTractList[c]\n",
    "    if allUnits[u] % 1 == 0:\n",
    "        unitVTDlist[u] = [allUnits[u]]\n",
    "        for i,uu in enumerate(surrounders):\n",
    "            if u == uu:\n",
    "                unitVTDlist[u].append(surroundedVTDs[i])\n",
    "\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        vtdList[t] += unitVTDlist[u]\n",
    "    #add more stuff here to convert to vtd lists\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":vtdList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"needsEnclaveRemoval.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "7a36c0ba-5a68-445b-a223-b7fa55dfd728",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are 10084 HD centers\n"
     ]
    }
   ],
   "source": [
    "nHDs = len(vtdGeom)\n",
    "print(\"there are\",nHDs,\"HD centers\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "1b794580-5a58-4238-b310-7c87872ed679",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this optional RESTART block pulls in an existing UNIT (not vtd) list for patching\n",
      "Must have already established unitGeoms, pops, topology -- or read in via next block\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the unpatched UNIT list file, e.g. ./2024state_HD_output/IL10084opt3ContigGoodPop.csv ./2024state_HD_output/IL10084opt3ContigGoodPop.csv\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sum of HDweight should be unity, actually is 0.9999999999999274\n",
      "I will now renormalize\n",
      "normalized weight is now 1.0\n",
      "I read in 10084 HD lists of units\n",
      "orig unit avg and sd usage are 1.00101 0.09408\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"this optional RESTART block pulls in an existing UNIT (not vtd) list for patching\") #vtdlist for patching\")\n",
    "print(\"Must have already established unitGeoms, pops, topology -- or read in via next block\")\n",
    "guessedFile = \"enter the unpatched UNIT list file, e.g. ./2024state_HD_output/\"+STATE+str(nHDs)+\"opt3ContigGoodPop.csv\"\n",
    "infile = input(guessedFile)\n",
    "inDF = pd.read_csv(infile)\n",
    "vtdListString = inDF[\"HDunitList\"]  #inDF[\"HDvtdList\"]\n",
    "nHDs = len(vtdListString)\n",
    "inVTDlist = [ast.literal_eval(vtdListString[t]) for t in range(nHDs)]\n",
    "HDweight = inDF[\"HDweight\"]\n",
    "sumWt = np.sum(HDweight)\n",
    "print(\"sum of HDweight should be unity, actually is\",sumWt)\n",
    "print(\"I will now renormalize\")\n",
    "HDweight = [HDweight[t] /sumWt for t in range(nHDs)]\n",
    "print(\"normalized weight is now\",np.sum(HDweight))\n",
    "HDvPop = inDF[\"HDvPop\"].to_list()\n",
    "hdCPx, hdCPy = inDF[\"centroid x\"], inDF[\"centroid y\"]\n",
    "hdCP = [Point(hdCPx[t], hdCPy[t]) for t in range(nHDs)]\n",
    "print(\"I read in\",nHDs,\"HD lists of units\") #vtds\")\n",
    "HDunitList = [inVTDlist[t].copy() for t in range(nHDs)]\n",
    "#HDunitList = [list() for t in range(nHDs)]\n",
    "#for t in range(nHDs):\n",
    "#    if t%500 == 0:\n",
    "#        print(\"working on converting HD\",t,\"from vtd list to unit list\")\n",
    "#    for v in inVTDlist[t]:  #this will skip over surrounded units, whose pops we have added to their surrounders\n",
    "#        if v in allUnits:\n",
    "#            HDunitList[t].append(allUnits.index(v))\n",
    "#    for c in unitCounties:\n",
    "#        if countyTractList[c][0] in inVTDlist[t]:\n",
    "#            u = allUnits.index(c+0.5)\n",
    "#            HDunitList[t].append(u)\n",
    "#    for j, L in enumerate(CCBlist):\n",
    "#        c = L[0]\n",
    "#        if countyTractList[c][0] in inVTDlist[t]:\n",
    "#            u = allUnits.index(j+0.25)\n",
    "#            HDunitList[t].append(u) \n",
    "            \n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse, bins=50, weights=unitPop,label=\"read-in\",histtype=\"step\")\n",
    "plt.legend()\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "print(\"orig unit avg and sd usage are\",r5(unpatchedAvg), r5(unpatchedSD) )\n",
    "plt.show()\n",
    "currAvg, currSD = unpatchedAvg, unpatchedSD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "id": "8014f0bf-74bb-40bc-b217-af4e204ea9a7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "upon restart, need to pull in unit topology and data\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the unpatched UNIT list file, e.g. ./state_map_files/MNunitTopologies_06Apr24.csv ./state_map_files/MNunitTopologies_06Apr24.csv\n"
     ]
    }
   ],
   "source": [
    "#SKIP THE BELOW IF NOT A COLD RESTART\n",
    "print(\"upon restart, need to pull in unit topology and data\")  #note, this won't have geometries for plotting, but fine for patching\n",
    "topologyFile = \"enter the unpatched UNIT list file, e.g. ./state_map_files/MNunitTopologies_06Apr24.csv\"\n",
    "infile = input(topologyFile)\n",
    "topDF = pd.read_csv(infile)\n",
    "unitCPx, unitCPy, unitPop = topDF[\"centroid x\"], topDF[\"centroid y\"], topDF[\"unitPop\"]\n",
    "nUnits = len(unitPop)\n",
    "unitCP = [Point(unitCPx[u], unitCPy[u]) for u in range(nUnits) ]\n",
    "onBorder = topDF[\"onBorder\"]\n",
    "borderSet = set()\n",
    "for i, onB in enumerate(onBorder):\n",
    "    if onB == 1:\n",
    "        borderSet.add(i)\n",
    "borderList = list(borderSet)\n",
    "\n",
    "nbrListString = topDF[\"neighborList\"]\n",
    "unitNbrs = [ast.literal_eval(nbrListString[u]) for u in range(nUnits)]\n",
    "unitParentVTDno = topDF[\"unitParentVTDno\"]  #NOTE: some units are VTD fragments, so they share a parentVTDno\n",
    "uVLstring = topDF[\"unitVTDlist\"]\n",
    "unitNbrs = [ast.literal_eval(uVLstring[u]) for u in range(nUnits)]\n",
    "allUnits = topDF[\"allUnits\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "5f3a5392-11f1-4061-a458-aecd834b2748",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working avg precinct-to-HDcP distance for HD 0\n",
      "working avg precinct-to-HDcP distance for HD 800\n",
      "working avg precinct-to-HDcP distance for HD 1600\n",
      "working avg precinct-to-HDcP distance for HD 2400\n",
      "working avg precinct-to-HDcP distance for HD 3200\n",
      "working avg precinct-to-HDcP distance for HD 4000\n",
      "working avg precinct-to-HDcP distance for HD 4800\n",
      "working avg precinct-to-HDcP distance for HD 5600\n",
      "working avg precinct-to-HDcP distance for HD 6400\n",
      "all avgDist to HD centers computed\n"
     ]
    }
   ],
   "source": [
    "#needed for restart only  about 5sec per 2000 HDs\n",
    "avgDist = [0. for t in range(nHDs)]\n",
    "popHDlist = list()\n",
    "for t in range(nHDs):\n",
    "    if t%800 == 0:\n",
    "        print(\"working avg precinct-to-HDcP distance for HD\",t)\n",
    "    if HDvPop[t] > 0.1 * aDP:\n",
    "        avgDist[t] = np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "        popHDlist.append(t)\n",
    "print(\"all avgDist to HD centers computed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "ea0db02f-9df8-4906-acb4-086c29c0fcc1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking for discontiguities for HD 500\n",
      "checking for discontiguities for HD 1000\n",
      "checking for discontiguities for HD 1500\n",
      "checking for discontiguities for HD 2000\n",
      "checking for discontiguities for HD 2500\n",
      "checking for discontiguities for HD 3000\n",
      "checking for discontiguities for HD 3500\n",
      "checking for discontiguities for HD 4000\n",
      "checking for discontiguities for HD 4500\n",
      "checking for discontiguities for HD 5000\n",
      "checking for discontiguities for HD 5500\n",
      "checking for discontiguities for HD 6000\n",
      "checking for discontiguities for HD 6500\n",
      "checking for discontiguities for HD 7000\n",
      "out of 6678 total HDs, there were 6678 0 0 0 HDs that were clean, discontig only, enclave-only, both problems.  Should all be zeroes\n"
     ]
    }
   ],
   "source": [
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()  #optional contiguity check\n",
    "for t in popHDlist:\n",
    "    if t%500 == 0:\n",
    "        print(\"checking for discontiguities for HD\",t)\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems.  Should all be zeroes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "27b42f93-dc87-4afe-8eb3-f30fdff4a737",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking unitUse, pop for county clusters\n",
      "9675 0.97942 211407.0\n",
      "9676 1.02596 82367.0\n",
      "9677 0.99889 83357.0\n"
     ]
    }
   ],
   "source": [
    "print(\"checking unitUse, pop for county clusters\")\n",
    "for uNo in allUnits:\n",
    "    if uNo - int(uNo) > 0.23 and uNo - int(uNo) < 0.27:\n",
    "        u = allUnits.index(uNo)\n",
    "        print(u,r5(unitUse[u]), unitPop[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "72941b8f-7be6-4a31-9377-618f44a34336",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "unpatchedUnitUse = unitUse.copy()              #... for safekeeping\n",
    "unpatchedHDlist =  [HDunitList[t].copy() for t in range(nHDs) ]\n",
    "unpatchedHDpop =   HDvPop.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "5f9ca091-1eb6-4135-a233-7f5ae0f5e3d1",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "unitUse = unpatchedUnitUse.copy()              #... for restarting\n",
    "HDunitList =  [unpatchedHDlist[t].copy() for t in range(nHDs) ]\n",
    "HDvPop =   unpatchedHDpop.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fc95ca58-c27f-4ac9-b6f7-234a94945f07",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fa2a97c4-11f3-48dd-b1b6-f7e98246dd8a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#for IL, only use avoidedEnclave / Island, not conventional patchUp method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "fd36caf6-71e4-44a4-9d09-7469512c5e05",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here, we exchange in under-used, THEN shed over-used.  Using new-for-WI avoidedEnclave routines\n",
      "Currently, we will stop patching when the overall sd of usage is less than 0.07\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated maxSD value 0.06\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this would currently cover a total of 2040 units\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated number of units to try boosting usage 120\n",
      "enter updated stopMinUse value for ending usage boost on a unit; I reco 0.97 0.98\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are currently 4328 units out of 9678 with usage below 0.98\n",
      "maxExchangePop is currently 0.05 fraction of avgDistrictPop\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter updated maxExchangePop fraction 0.05\n",
      "enter 1 to print out stats for every patched HD, otherwise enter reporting frequency; e.g. 10 10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let's further tighten the distro with exchanges up to 37683\n",
      "current avg and SD of unit usage are 1.00101 0.09408 . Now trying to increase up to 120 units' underusage\n",
      "all done trying to increase usage of unit 9566 final usage = 0.73776 228 sec elapsed 45 1 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00101 0.09377\n",
      "all done trying to increase usage of unit 4414 final usage = 0.75313 349 sec elapsed 17 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00101 0.09353\n",
      "all done trying to increase usage of unit 9666 final usage = 0.87257 989 sec elapsed 137 60 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00102 0.09218\n",
      "all done trying to increase usage of unit 4189 final usage = 0.76511 1120 sec elapsed 18 1 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00102 0.09201\n",
      "all done trying to increase usage of unit 9568 final usage = 0.82251 1646 sec elapsed 98 12 successful, failed patches, couldn't start= 7\n",
      "current avg and SD of usage are 1.00102 0.09134\n",
      "all done trying to increase usage of unit 4413 final usage = 0.82303 1795 sec elapsed 33 6 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00102 0.09091\n",
      "all done trying to increase usage of unit 4190 final usage = 0.78212 1917 sec elapsed 23 5 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 1.00102 0.09069\n",
      "all done trying to increase usage of unit 1189 final usage = 0.85933 2113 sec elapsed 83 8 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00102 0.08963\n",
      "all done trying to increase usage of unit 4191 final usage = 0.82068 2276 sec elapsed 33 20 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00102 0.0893\n",
      "begin usage increase for unit 4192 with usage 0.75508 . Sec, total UU units tried = 2288 10\n",
      "all done trying to increase usage of unit 4192 final usage = 0.82924 2455 sec elapsed 34 17 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00102 0.08905\n",
      "all done trying to increase usage of unit 2049 final usage = 0.91758 2623 sec elapsed 70 32 successful, failed patches, couldn't start= 19\n",
      "current avg and SD of usage are 1.00101 0.08797\n",
      "all done trying to increase usage of unit 4420 final usage = 0.81555 2782 sec elapsed 27 12 successful, failed patches, couldn't start= 13\n",
      "current avg and SD of usage are 1.00101 0.08781\n",
      "all done trying to increase usage of unit 4403 final usage = 0.82511 2943 sec elapsed 30 9 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00101 0.08762\n",
      "all done trying to increase usage of unit 9598 final usage = 0.84207 3344 sec elapsed 83 6 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 1.00101 0.08711\n",
      "all done trying to increase usage of unit 9524 final usage = 0.98047 3414 sec elapsed 102 22 successful, failed patches, couldn't start= 8\n",
      "current avg and SD of usage are 1.001 0.08503\n",
      "all done trying to increase usage of unit 2844 final usage = 0.89999 3614 sec elapsed 112 50 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.001 0.08428\n",
      "all done trying to increase usage of unit 1222 final usage = 0.98024 3735 sec elapsed 164 7 successful, failed patches, couldn't start= 6\n",
      "current avg and SD of usage are 1.00101 0.0827\n",
      "all done trying to increase usage of unit 4186 final usage = 0.8107 3796 sec elapsed 23 26 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00101 0.08249\n",
      "all done trying to increase usage of unit 9608 final usage = 0.86897 4097 sec elapsed 98 31 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00101 0.08175\n",
      "begin usage increase for unit 2071 with usage 0.76894 . Sec, total UU units tried = 4101 20\n",
      "all done trying to increase usage of unit 2071 final usage = 0.986 4240 sec elapsed 187 20 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.001 0.07903\n",
      "all done trying to increase usage of unit 4237 final usage = 0.88689 4303 sec elapsed 53 17 successful, failed patches, couldn't start= 18\n",
      "current avg and SD of usage are 1.001 0.07843\n",
      "all done trying to increase usage of unit 9554 final usage = 0.92266 4597 sec elapsed 145 49 successful, failed patches, couldn't start= 59\n",
      "current avg and SD of usage are 1.001 0.07732\n",
      "all done trying to increase usage of unit 4196 final usage = 0.84737 4660 sec elapsed 30 13 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.001 0.07716\n",
      "all done trying to increase usage of unit 4216 final usage = 0.89392 4741 sec elapsed 51 60 successful, failed patches, couldn't start= 11\n",
      "current avg and SD of usage are 1.00099 0.07657\n",
      "all done trying to increase usage of unit 1207 final usage = 0.94084 4964 sec elapsed 130 81 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00099 0.07572\n",
      "all done trying to increase usage of unit 4194 final usage = 0.84484 5048 sec elapsed 28 27 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00099 0.07561\n",
      "all done trying to increase usage of unit 4195 final usage = 0.8472 5127 sec elapsed 29 26 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00099 0.07552\n",
      "all done trying to increase usage of unit 4197 final usage = 0.8472 5209 sec elapsed 29 26 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00099 0.07545\n",
      "all done trying to increase usage of unit 4193 final usage = 0.84482 5290 sec elapsed 28 27 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00099 0.07536\n",
      "begin usage increase for unit 8342 with usage 0.78571 . Sec, total UU units tried = 5294 30\n",
      "all done trying to increase usage of unit 8342 final usage = 0.98041 5644 sec elapsed 173 30 successful, failed patches, couldn't start= 21\n",
      "current avg and SD of usage are 1.00099 0.07424\n",
      "all done trying to increase usage of unit 2064 final usage = 0.98333 5793 sec elapsed 174 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00099 0.0733\n",
      "all done trying to increase usage of unit 2843 final usage = 0.97734 6134 sec elapsed 136 54 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00099 0.07258\n",
      "all done trying to increase usage of unit 2874 final usage = 0.9443 6517 sec elapsed 114 79 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00099 0.07211\n",
      "all done trying to increase usage of unit 4182 final usage = 0.88725 6601 sec elapsed 54 30 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 1.00099 0.07174\n",
      "all done trying to increase usage of unit 9575 final usage = 0.88117 6753 sec elapsed 81 7 successful, failed patches, couldn't start= 38\n",
      "current avg and SD of usage are 1.00099 0.07106\n",
      "all done trying to increase usage of unit 2066 final usage = 0.98052 6889 sec elapsed 163 1 successful, failed patches, couldn't start= 11\n",
      "current avg and SD of usage are 1.00099 0.07022\n",
      "all done trying to increase usage of unit 4198 final usage = 0.91277 6971 sec elapsed 50 3 successful, failed patches, couldn't start= 12\n",
      "current avg and SD of usage are 1.00099 0.06992\n",
      "all done trying to increase usage of unit 4409 final usage = 0.88715 7063 sec elapsed 38 33 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00099 0.0698\n",
      "all done trying to increase usage of unit 4410 final usage = 0.88751 7163 sec elapsed 38 33 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00099 0.06966\n",
      "begin usage increase for unit 2768 with usage 0.8036 . Sec, total UU units tried = 7170 40\n",
      "all done trying to increase usage of unit 2768 final usage = 0.98068 7782 sec elapsed 125 19 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00099 0.0692\n",
      "all done trying to increase usage of unit 8599 final usage = 0.94894 7978 sec elapsed 65 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00098 0.06788\n",
      "all done trying to increase usage of unit 4407 final usage = 0.98008 8253 sec elapsed 85 9 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00098 0.0674\n",
      "all done trying to increase usage of unit 2774 final usage = 0.98086 9229 sec elapsed 129 67 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00098 0.06697\n",
      "all done trying to increase usage of unit 3033 final usage = 0.98023 9875 sec elapsed 123 13 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00098 0.06653\n",
      "all done trying to increase usage of unit 3096 final usage = 0.98073 10089 sec elapsed 88 1 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00098 0.06501\n",
      "all done trying to increase usage of unit 4401 final usage = 0.98123 10266 sec elapsed 85 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00098 0.064\n",
      "all done trying to increase usage of unit 1249 final usage = 0.98153 11111 sec elapsed 133 82 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00097 0.06338\n",
      "all done trying to increase usage of unit 4185 final usage = 0.95267 11411 sec elapsed 64 29 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00097 0.06303\n",
      "all done trying to increase usage of unit 1038 final usage = 0.98201 11635 sec elapsed 85 4 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00097 0.06169\n",
      "begin usage increase for unit 2825 with usage 0.823 . Sec, total UU units tried = 11647 50\n",
      "all done trying to increase usage of unit 2825 final usage = 0.98189 12227 sec elapsed 116 8 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00097 0.06137\n",
      "all done trying to increase usage of unit 4214 final usage = 0.90421 12308 sec elapsed 39 9 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00097 0.0612\n",
      "all done trying to increase usage of unit 4112 final usage = 0.98026 12398 sec elapsed 77 28 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00097 0.0606\n",
      "all done trying to increase usage of unit 4111 final usage = 0.98025 12495 sec elapsed 77 26 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00096 0.06017\n",
      "all done trying to increase usage of unit 2335 final usage = 0.88613 12573 sec elapsed 47 21 successful, failed patches, couldn't start= 26\n",
      "current avg and SD of usage are 1.00097 0.05991\n"
     ]
    }
   ],
   "source": [
    "#NEW for WI - faster: use the avoidedEnclave, avoidedIsland subroutines vs. wontEnclave\n",
    "\n",
    "#FIRST PATCHING BLOCK - boosting underuse.  Suppresses long strings.  For some states (e.g. MA), do overused first. MA:over-und-over-und\n",
    "print(\"Here, we exchange in under-used, THEN shed over-used.  Using new-for-WI avoidedEnclave routines\")\n",
    "maxSD = 0.07  #0.07  #0.05   #adjust down if distro already tight\n",
    "print(\"Currently, we will stop patching when the overall sd of usage is less than\",maxSD)\n",
    "maxSD = float(input(\"enter updated maxSD value\"))\n",
    "stopMinUse = 1. - maxSD\n",
    "#print(\"we will stop patching on individual underused units when their usage exceeds\",r5(stopMinUse))\n",
    "maxNtries = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        maxNtries +=1\n",
    "print(\"this would currently cover a total of\",maxNtries,\"units\")\n",
    "maxNtries = int(input(\"enter updated number of units to try boosting usage\"))\n",
    "stopMinUse = float(input(\"enter updated stopMinUse value for ending usage boost on a unit; I reco 0.97\"))\n",
    "nInPlay = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        nInPlay +=1\n",
    "print(\"there are currently\",nInPlay,\"units out of\",nUnits,\"with usage below\",stopMinUse)\n",
    "nSmallUsers = 5\n",
    "maxExchangePop = 0.05*aDP \n",
    "print(\"maxExchangePop is currently\",r5(maxExchangePop/aDP),\"fraction of avgDistrictPop\")\n",
    "newMEPratio = float(input(\"Enter updated maxExchangePop fraction\"))\n",
    "maxExchangePop = newMEPratio*aDP\n",
    "debug1 = int(input(\"enter 1 to print out stats for every patched HD, otherwise enter reporting frequency; e.g. 10\"))\n",
    "print(\"Let's further tighten the distro with exchanges up to\",int(maxExchangePop)) #1/25/24\n",
    "maxGap = 0.9 * np.median(unitPop) \n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "\n",
    "attemptedSmallUs, startTime = list(), time.time()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to increase up to\",maxNtries,\"units' underusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedSmallUs) < maxNtries: \n",
    "    #each round, find the (5) most underused not-yet-tried units. Pick the unit w/ most overuse of it + 1-nbrs\n",
    "    idx = np.argsort(unitUse)\n",
    "    idxNo, nSmallFound, smallUsers = 0,0,list()\n",
    "    while nSmallFound < nSmallUsers:\n",
    "        consideredSmallU = idx[idxNo]\n",
    "        if consideredSmallU not in attemptedSmallUs:\n",
    "            smallUsers.append(consideredSmallU)\n",
    "            nSmallFound +=1\n",
    "        idxNo +=1\n",
    "    UUUclusters = [ [b] + unitNbrs[b] for b in smallUsers ]\n",
    "    smallUnderUse = [np.sum([(unitUse[j] - 1.) for j in UUUclusters[i] ]) for i in range(nSmallUsers) ]\n",
    "    smallI = smallUnderUse.index(np.max(smallUnderUse))\n",
    "    UUU = smallUsers[ smallI ]  #pick the unit that centers cluster with least composite use\n",
    "    attemptedSmallUs.append(UUU)  #so we don't try this unit again in a future loop\n",
    "    UUUc = UUUclusters[smallI]  #the list of this unit and ALL its neighbors (to be curated below ...)\n",
    "    if len(attemptedSmallUs) % debug1 == 0:\n",
    "        print(\"begin usage increase for unit\",UUU,\"with usage\",r5(unitUse[UUU]),\". Sec, total UU units tried =\",\n",
    "              int(time.time()-startTime),len(attemptedSmallUs) )\n",
    "    for u in UUUc.copy():\n",
    "        if unitUse[u] > 1.:\n",
    "            UUUc.remove(u)  #...drop any overused neighbors of the primary UUU from the target sheddable cluster\n",
    "    uuuHDs, uuuDists = list(), list()\n",
    "    for t in popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if UUU not in HDunitList[t]:\n",
    "            HDadjoinSet = set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(UUUc) ) > 0: #the UUU or one of its underused 1-neighbors adjoins this HD\n",
    "                uuuHDs.append(t)  #Note: we'll check later if we can contiguously pick up the UUU's cluster\n",
    "                uuuDists.append( unitCP[UUU].distance(hdCP[t]) / avgDist[t] )\n",
    "        idx0 = np.argsort(uuuDists)\n",
    "    hasCandidates = True\n",
    "    if len(uuuDists) == 0:  #this underused unit is buried inside others; skip it\n",
    "        hasCandidates = False\n",
    "        print(\"   Couldn't find any HDs adjacent to underused unit\",UUU)\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo = 0,0,0,-1\n",
    "    while unitUse[UUU] < stopMinUse and idxNo < 0.8*len(uuuHDs) and hasCandidates: #arbitrarily only examine 80% closest of HDs\n",
    "        excess, giveUpOnShedding = 99*aDP, True  #default = failed swap\n",
    "        idxNo += 1\n",
    "        if idxNo % 20 == 0 and debug1 == 1:\n",
    "            print(\"try to add unit\",UUU,\"from\",abs(idxNo),\"th HD.  Usage up to\",unitUse[UUU] )\n",
    "        t = uuuHDs[idx0[idxNo]]\n",
    "        trySet = set(HDunitList[t]).union(set(UUUc))\n",
    "        complementContig = avoidedEnclave(HDunitList[t], unitNbrs, UUUc)\n",
    "        #contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        loopUUUc = UUUc.copy()  #default; we will add whole cluster\n",
    "        if not complementContig: #we can't add whole cluster; neighbors may be enclavy.   Try just adding the UUU\n",
    "            trySet = set(HDunitList[t]).union({UUU})\n",
    "            complementContig  = avoidedEnclave(HDunitList[t], unitNbrs, [UUU])\n",
    "            loopUUUc = [UUU]\n",
    "        if complementContig:  #we can at least add the cluster, let's go for more\n",
    "            HDuuuSet = set(loopUUUc).difference(set(HDunitList[t]))  #the subset of the UUU cluster that adjoins (NOT in) this HD\n",
    "            HDuuuCpop = np.sum([unitPop[u] for u in HDuuuSet])\n",
    "            giveUpOnAdding = False            \n",
    "            addCandidates, addUseDists = list(), list()\n",
    "            uuCandidates = getAdjoiners(trySet, unitNbrs)  #any adjoiner can be picked up, even if far from UUUc\n",
    "            for u in uuCandidates:\n",
    "                if HDuuuCpop + unitPop[u] <= maxExchangePop:\n",
    "                    addCandidates.append(u)  #Below's relative scoring of use and distance is a bit arbitrary\n",
    "                    addUseDists.append((unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t])  #bias toward close, underused\n",
    "            if len(addCandidates) == 0:\n",
    "                giveUpOnAdding = True\n",
    "            while HDuuuCpop < maxExchangePop and not giveUpOnAdding:\n",
    "                addNneighbors = [len( set(unitNbrs[addC]).intersection(trySet) ) for addC in addCandidates ]\n",
    "                addScores = addUseDists.copy()\n",
    "                for jjj, u in enumerate(addCandidates):\n",
    "                    if addNneighbors[jjj] == 1:\n",
    "                        addScores[jjj] += 0.4321    #discourage growing fingers\n",
    "                #print(\"HDuuuCpop is now\",HDuuuCpop)\n",
    "                idx, ij, notYetPicked = np.argsort(addScores), 0, True\n",
    "                while ij < 0.5*len(addScores) and notYetPicked:\n",
    "                    listNo = idx[ij]   #work from low to high score\n",
    "                    addU = addCandidates[listNo]\n",
    "                    cContig = avoidedEnclave(list(trySet), unitNbrs, [addU])\n",
    "                    #cContig = wontEnclave(addU, list(trySet), unitNbrs, borderUnits)  #4/20/24 sub this in as faster? vs below line\n",
    "                    #contig,cContig, __, ___ = enclaveCheck(list(trySet.union({addU}) ), unitNbrs)  #4/20/24 this is unnec slow\n",
    "                    if cContig: #contig and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDuuuCpop += unitPop[addU]\n",
    "                        HDuuuSet.add(addU)\n",
    "                        trySet.add(addU)\n",
    "                        del addUseDists[addCandidates.index(addU)]\n",
    "                        del addCandidates[addCandidates.index(addU)]                        \n",
    "                        for uu in list(set(unitNbrs[addU]).difference(trySet) ): \n",
    "                            if uu not in addCandidates and unitPop[uu] + HDuuuCpop < maxExchangePop and unitUse[uu] < 1.01:\n",
    "                                addCandidates.append(uu)\n",
    "                                addUseDists.append( (unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnAdding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            addSet = HDuuuSet.copy()  #we're done building the list of underused units to add to this HD\n",
    "            trySet = set(HDunitList[t]).union(addSet) \n",
    "            excess = np.sum([unitPop[u] for u in trySet]) - aDP\n",
    "            shedCandidates, shedScores, giveUpOnShedding = list(), list(), False\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if unitPop[u] <= excess + maxGap:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward OVERUSED, far\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            shedSet = set()\n",
    "            while excess > maxGap and not giveUpOnShedding:\n",
    "                #print(\"excess pop is now\",excess,\"for HD\",t)\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    if excess - unitPop[shedU] >= -1*maxGap:\n",
    "                        cContig = avoidedIsland(list(trySet), unitNbrs, [shedU])\n",
    "                        #contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                        if cContig: # and contig :\n",
    "                            notYetPicked = False\n",
    "                            excess -= unitPop[shedU]\n",
    "                            trySet.remove(shedU)\n",
    "                            shedSet.add(shedU)\n",
    "                            del shedScores[shedCandidates.index(shedU)]\n",
    "                            del shedCandidates[shedCandidates.index(shedU)]\n",
    "                            newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                            for u in newSheddables:\n",
    "                                if excess - unitPop[u] >= -1*maxGap and u not in shedCandidates:\n",
    "                                    shedCandidates.append(u)  #we'll check enclavity if ever picked\n",
    "                                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                            for kkk, u in enumerate(shedCandidates): #checking if this shed eliminates high-pop future sheds ...\n",
    "                                if excess - unitPop[u] < -1*maxGap:\n",
    "                                    del shedScores[kkk]\n",
    "                                    del shedCandidates[kkk]\n",
    "                    ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all shedcandidates would create a discontig, so can't shed enough units to square pop\n",
    "            legitSwap = False\n",
    "            if abs(excess) <= 2.*maxGap:  #giving ourselves a bit more margin after exchanges\n",
    "                contig,cContig, __, ___ = enclaveCheck(list(trySet), unitNbrs) \n",
    "                if contig and cContig:\n",
    "                    legitSwap = True\n",
    "            if legitSwap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t] = np.sum([ unitPop[u] for u in HDunitList[t] ])\n",
    "                nPatchSuccess +=1\n",
    "                #print(\"we added\",addSet,\"and shed units\",shedSet,\"from HD\",t)\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "        else:  #adding neither the UUU cluster or just the UUU worked; couldn't even start\n",
    "            nCouldntStart +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "\n",
    "    print(\"all done trying to increase usage of unit\",UUU,\"final usage =\",r5(unitUse[UUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"successful, failed patches, couldn't start=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "861f29d3-b727-49af-90a8-aa9a963e0741",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unpatched, patched use avgs are 1.00101 1.00097 and their SDs are 0.09408 0.05991\n",
      "And here is the pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": 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tBYDrOIUEAACsQ4ABAADWIcAAAADrNCrAPP/88+rfv798Pp98Pp/8fr/effddZ/vRo0eVkZGhDh06qE2bNkpPT1dxcXHQPgoLC5WWlqaYmBjFx8dr8uTJqq6uDpqzZs0aDRgwQF6vVz179lRmZmbTOwQAAM1OowJM165dNWfOHOXl5WnTpk265pprNHLkSG3btk2SNHHiRL399ttavny51q5dq/379+vGG290Xl9TU6O0tDRVVlZq3bp1eumll5SZmakZM2Y4c/bs2aO0tDQNHTpU+fn5mjBhgu6++26tWrXqDLUMAABs5zHGmNPZQfv27fX444/rpptuUqdOnbR06VLddNNNkqSdO3eqT58+ys3N1eDBg/Xuu+/quuuu0/79+5WQkCBJWrRokaZOnaqvv/5akZGRmjp1qrKyslRQUOB8j1tvvVWlpaVauXLlKdcVCAQUGxursrIy+Xy+02kRQCioPiIta1M3vvmwekxf42o5TbF3TprbJQAh71R/fzf5Gpiamhq99tprOnLkiPx+v/Ly8lRVVaWUlBRnTu/evdW9e3fl5uZKknJzc9WvXz8nvEhSamqqAoGAcxQnNzc3aB/1c+r38UMqKioUCASCFgDNSFiUNOyDuoWPEgBavEYHmK1bt6pNmzbyer0aP3683njjDSUnJ6uoqEiRkZGKi4sLmp+QkKCioiJJUlFRUVB4qd9ev+3H5gQCAZWXl/9gXbNnz1ZsbKyzdOvWrbGtAQhlYeFSwtV1S1i429UAcFmjA0yvXr2Un5+vDRs26L777tOYMWO0ffv2s1Fbo0ybNk1lZWXOsm/fPrdLAgAAZ0mjn8QbGRmpnj17SpIGDhyojRs3av78+brllltUWVmp0tLSoKMwxcXFSkxMlCQlJibq008/Ddpf/V1Kx8/5/p1LxcXF8vl8io6O/sG6vF6vvF5vY9sBYIvaKmn3f9WNe97rbi0AXHfaz4Gpra1VRUWFBg4cqFatWiknJ8fZtmvXLhUWFsrv90uS/H6/tm7dqpKSEmdOdna2fD6fkpOTnTnH76N+Tv0+ALRQtZXSpgfqltpKt6sB4LJGHYGZNm2aRowYoe7du+vQoUNaunSp1qxZo1WrVik2Nlbjxo3TpEmT1L59e/l8Pj344IPy+/0aPHiwJGn48OFKTk7WHXfcoblz56qoqEjTp09XRkaGc/Rk/Pjxeu655zRlyhSNHTtWq1ev1rJly5SVlXXmuwcAAFZqVIApKSnRnXfeqQMHDig2Nlb9+/fXqlWr9Mtf/lKSNG/ePIWFhSk9PV0VFRVKTU3VwoULndeHh4drxYoVuu++++T3+9W6dWuNGTNGs2bNcuYkJSUpKytLEydO1Pz589W1a1e98MILSk1NPUMtAwAA2532c2BCFc+BAZoZngMDtAhn/TkwAAAAbiHAAAAA6xBgAACAdRr9HBgAcEWYV7pqxbExgBaNAAPADmER0k+4CBZAHU4hAQAA63AEBoAdaqukva/UjXuMdrcWAK4jwACwQ22ltP6uunH3f3K3FgCu4xQSAACwDgEGAABYhwADAACsQ4ABAADWIcAAAADrEGAAAIB1uI0agB3CvNIVy46NAbRoBBgAdgiL4PkvABycQgIAANbhCAwAO9RWS399o27c9QZ3awHgOgIMADvUVkgf31w3vvmwu7UAcB2nkAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWIcAAwAArMNt1ADsEBYpDV5ybAygRSPAALBDWCvp/F+7XQWAEMEpJAAAYB2OwACwQ221dGBV3bhzqru1AHAdAQaAHWorpLXX1Y35KAGgxeMUEgAAsA4BBgAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdbiNGoAdwiKlS587NgbQohFgANghrJV0YYbbVQAIEZxCAgAA1uEIDAA71NZIX39UN+50pbu1AHAdAQaAHWqPSjlD68Z8lADQ4nEKCQAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdQgwAADAOtxGDcAOnlbSJXOPjQG0aAQYAHYIj5SSJ7tdBYAQwSkkAABgHY7AALBDbY307Wd143YD3K0FgOsIMADU4+Est0s4qWjPUe3od5Mkqc/W/5UU5W5BAFzFKSQAAGAdAgwAALAOAQYAAFinUQFm9uzZ+vnPf662bdsqPj5e119/vXbt2hU05+jRo8rIyFCHDh3Upk0bpaenq7i4OGhOYWGh0tLSFBMTo/j4eE2ePFnV1dVBc9asWaMBAwbI6/WqZ8+eyszMbFqHAACg2WlUgFm7dq0yMjK0fv16ZWdnq6qqSsOHD9eRI0ecORMnTtTbb7+t5cuXa+3atdq/f79uvPFGZ3tNTY3S0tJUWVmpdevW6aWXXlJmZqZmzJjhzNmzZ4/S0tI0dOhQ5efna8KECbr77ru1atWqM9AyAACwnccYY5r64q+//lrx8fFau3athgwZorKyMnXq1ElLly7VTTfV3S2wc+dO9enTR7m5uRo8eLDeffddXXfdddq/f78SEhIkSYsWLdLUqVP19ddfKzIyUlOnTlVWVpYKCgqc73XrrbeqtLRUK1euPKXaAoGAYmNjVVZWJp/P19QWgRbBxruQyo19dyHtnZPmdglAyDvV39+ndQ1MWVmZJKl9+/aSpLy8PFVVVSklJcWZ07t3b3Xv3l25ubmSpNzcXPXr188JL5KUmpqqQCCgbdu2OXOO30f9nPp9nEhFRYUCgUDQAqD5qFa4ni4epaeLR6la4W6XA8BlTX4OTG1trSZMmKDLL79cF110kSSpqKhIkZGRiouLC5qbkJCgoqIiZ87x4aV+e/22H5sTCARUXl6u6OjoBvXMnj1bjz76aFPbARDiqkwrPV082u0yAISIJh+BycjIUEFBgV577bUzWU+TTZs2TWVlZc6yb98+t0sCAABnSZOOwDzwwANasWKFPvzwQ3Xt2tVZn5iYqMrKSpWWlgYdhSkuLlZiYqIz59NPPw3aX/1dSsfP+f6dS8XFxfL5fCc8+iJJXq9XXq+3Ke0AsIBHterprfvDZHdFNxmeAgG0aI16BzDG6IEHHtAbb7yh1atXKykpKWj7wIED1apVK+Xk5Djrdu3apcLCQvn9fkmS3+/X1q1bVVJS4szJzs6Wz+dTcnKyM+f4fdTPqd8HgJYnylOp7F4Zyu6VoShPpdvlAHBZo47AZGRkaOnSpXrrrbfUtm1b55qV2NhYRUdHKzY2VuPGjdOkSZPUvn17+Xw+Pfjgg/L7/Ro8eLAkafjw4UpOTtYdd9yhuXPnqqioSNOnT1dGRoZzBGX8+PF67rnnNGXKFI0dO1arV6/WsmXLlJUV+ndKAACAs69RR2Cef/55lZWV6eqrr1bnzp2d5fXXX3fmzJs3T9ddd53S09M1ZMgQJSYm6o9//KOzPTw8XCtWrFB4eLj8fr9uv/123XnnnZo1a5YzJykpSVlZWcrOztbFF1+sJ598Ui+88IJSU1PPQMsAAMB2p/UcmFDGc2CAU8dzYM4NngMDnNw5eQ4MAACAGwgwAADAOgQYAABgnSY/iRcAzqVqhet3X9/ojAG0bAQYAFaoMq00+8BYt8sAECI4hQQAAKzDERgAVvCoVj9p9bUk6W9VnfgoAaCFI8AAsEKUp1If9xknyd7nwAA4c/gTBgAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdQgwAADAOtxGDcAKNQrXy39Pc8YAWjYCDAArVJpWmrH/PrfLABAiOIUEAACswxEYAJYwah8ekCQdrPFJ8rhbDgBXEWAAWCHaU6HP+o6WxEcJAOAUEgAAsBABBgAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdbiNGoAVahSu/z04zBkDaNkIMACsUGla6V//OtHtMgCECE4hAQAA63AEBoAljKI9FZKkcuMVHyUAtGwcgQFghWhPhXb0u0k7+t3kBBkALRcBBgAAWIcAAwAArEOAAQAA1iHAAAAA63AXEgCcIz0eznK7hEbbOyfN7RKAE+IIDAAAsA5HYABYoVZhyiq93BkDaNkIMACsUGEilVE4ze0yAIQI/owBAADWIcAAAADrEGAAWCHac1R7+1+nvf2vU7TnqNvlAHAZAQYAAFiHAAMAAKxDgAEAANYhwAAAAOsQYAAAgHUIMAAAwDo8iReAFWoVptWBS50xgJaNAAPAChUmUmP3PuJ2GQBCBH/GAAAA6xBgAACAdQgwAKwQ7Tmq7Rela/tF6XyUAACugQFgj5iwCrdLABAiOAIDAACsQ4ABAADWaXSA+fDDD/UP//AP6tKlizwej958882g7cYYzZgxQ507d1Z0dLRSUlL0xRdfBM05ePCgRo8eLZ/Pp7i4OI0bN06HDx8OmrNlyxZdeeWVioqKUrdu3TR37tzGdwcAAJqlRgeYI0eO6OKLL9aCBQtOuH3u3Ll65plntGjRIm3YsEGtW7dWamqqjh49dtHd6NGjtW3bNmVnZ2vFihX68MMPde+99zrbA4GAhg8frvPOO095eXl6/PHH9cgjj+i//uu/mtAiAABobhp9Ee+IESM0YsSIE24zxujpp5/W9OnTNXLkSEnSyy+/rISEBL355pu69dZbtWPHDq1cuVIbN27UpZfWPVXz2Wef1a9+9Ss98cQT6tKli1555RVVVlbqxRdfVGRkpPr27av8/Hw99dRTQUEHAAC0TGf0Gpg9e/aoqKhIKSkpzrrY2FgNGjRIubm5kqTc3FzFxcU54UWSUlJSFBYWpg0bNjhzhgwZosjISGdOamqqdu3apW+//faE37uiokKBQCBoAdB81Mqj9Ycv0vrDF6lWHrfLAeCyM3obdVFRkSQpISEhaH1CQoKzraioSPHx8cFFRESoffv2QXOSkpIa7KN+W7t27Rp879mzZ+vRRx89M40ACDkVxqtbv5rjdhkAQkSzuQtp2rRpKisrc5Z9+/a5XRIAADhLzmiASUxMlCQVFxcHrS8uLna2JSYmqqSkJGh7dXW1Dh48GDTnRPs4/nt8n9frlc/nC1oAAEDzdEYDTFJSkhITE5WTk+OsCwQC2rBhg/x+vyTJ7/ertLRUeXl5zpzVq1ertrZWgwYNcuZ8+OGHqqqqcuZkZ2erV69eJzx9BKD5i/YcVV7ybcpLvo2PEgDQ+ABz+PBh5efnKz8/X1Ldhbv5+fkqLCyUx+PRhAkT9B//8R/605/+pK1bt+rOO+9Uly5ddP3110uS+vTpo2uvvVb33HOPPv30U33yySd64IEHdOutt6pLly6SpNtuu02RkZEaN26ctm3bptdff13z58/XpEmTzljjAOzTISKgDhFcoA+gCRfxbtq0SUOHDnW+rg8VY8aMUWZmpqZMmaIjR47o3nvvVWlpqa644gqtXLlSUVFRzmteeeUVPfDAAxo2bJjCwsKUnp6uZ555xtkeGxur9957TxkZGRo4cKA6duyoGTNmcAs1AACQJHmMMcbtIs6GQCCg2NhYlZWVcT0McBI9Hs5yu4STivYc1Y5+N0mS+mz9X5WbqJO8AmfC3jlpbpeAFuZUf383m7uQAABAy0GAAQAA1iHAAAAA65zRJ/ECwNlSK482f3eBMwbQshFgAFihwng1cvc8t8sAECI4hQQAAKxDgAEAANYhwACwQpTnqD7uPVYf9x6rKD5KAGjxuAYGgBU8krpGljhjAC0bR2AAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHu5AAWMFI+vPR7s4YQMtGgAFghaMmSsP/vNDtMgCECE4hAQAA6xBgAACAdQgwAKwQ5Tmq9y68X+9deD8fJQCAa2AA2MEj6cKoQmcMoGXjCAwAALAOAQYAAFiHAAMAAKxDgAEAANYhwAAAAOtwFxIAKxhJf62Md8YAWjYCDAArHDVRumLni26XASBEcAoJAABYhwADAACsQ4ABYAWvp0Jv9Zyot3pOlNdT4XY5AFzGNTAArBAmo4tjvnDGAFo2jsAAAADrEGAAAIB1CDAAAMA6BBgAAGAdAgwAALAOdyEBsMY31T63SwAQIggwAKxQbqI0cPtSt8tocXo8nOV2CY22d06a2yXgHOAUEgAAsA4BBgAAWIcAA8AKXk+FXjv/Yb12/sN8lAAAroEBYIcwGQ1uU+CMAbRsBBjgDLPxokcAsA2nkAAAgHUIMAAAwDoEGAAAYB2ugUFI43oSAMCJEGAAWOO7Wq/bJQAIEQQYAFYoN1FKLviD22UACBEEGABAs2LjqWc+v6nxuIgXAABYhyMwLYSNf5EAx/N6KvX8eb+VJN33l39ThYl0uSIAbiLAALBCmGp1jW+TMwbQshFgAABwmY1Hyd2+bocA0wQ2/qABANCchPRFvAsWLFCPHj0UFRWlQYMG6dNPP3W7JAAAEAJCNsC8/vrrmjRpkmbOnKnPPvtMF198sVJTU1VSUuJ2aQAAwGUhG2Ceeuop3XPPPbrrrruUnJysRYsWKSYmRi+++KLbpQEAAJeF5DUwlZWVysvL07Rp05x1YWFhSklJUW5u7glfU1FRoYqKCufrsrIySVIgEDjj9dVWfHfG9wngx9V4jirwf//r1VR8p1rDnUiAm87G79fj92uM+dF5IRlg/v73v6umpkYJCQlB6xMSErRz584Tvmb27Nl69NFHG6zv1q3bWakRwLkX64zudLEKAJIU+/TZ3f+hQ4cUGxv7g9tDMsA0xbRp0zRp0iTn69raWh08eFAdOnSQx+Np1L4CgYC6deumffv2yefznelSQw79Nn8trWf6bf5aWs8tqV9jjA4dOqQuXbr86LyQDDAdO3ZUeHi4iouLg9YXFxcrMTHxhK/xer3yeoM/qTYuLu606vD5fM3+B+V49Nv8tbSe6bf5a2k9t5R+f+zIS72QvIg3MjJSAwcOVE5OjrOutrZWOTk58vv9LlYGAABCQUgegZGkSZMmacyYMbr00kt12WWX6emnn9aRI0d01113uV0aAABwWcgGmFtuuUVff/21ZsyYoaKiIl1yySVauXJlgwt7zwav16uZM2c2OCXVXNFv89fSeqbf5q+l9dzS+j0VHnOy+5QAAABCTEheAwMAAPBjCDAAAMA6BBgAAGAdAgwAALCOlQGmR48e8ng8DZaMjIygecYYjRgxQh6PR2+++WaD/WRmZqp///6KiopSfHx8g9dv2bJFV155paKiotStWzfNnTu3wT6WL1+u3r17KyoqSv369dM777zToIYZM2aoc+fOio6OVkpKir744otz3u/GjRs1bNgwxcXFqV27dkpNTdXmzZut7Pfqq69usG38+PFB+ygsLFRaWppiYmIUHx+vyZMnq7q6OmjOmjVrNGDAAHm9XvXs2VOZmZkNalmwYIF69OihqKgoDRo0SJ9++mnQ9qNHjyojI0MdOnRQmzZtlJ6e3uABjOei582bN2vUqFHq1q2boqOj1adPH82fP7/B9wmVns/Ev3G9b775Rl27dpXH41FpaWmz7re5vGedSr82vWedSs+SlJubq2uuuUatW7eWz+fTkCFDVF5e7mw/ePCgRo8eLZ/Pp7i4OI0bN06HDx8O2Z5dZyxUUlJiDhw44CzZ2dlGkvnggw+C5j311FNmxIgRRpJ54403grY9+eSTpkuXLuaVV14xu3fvNps3bzZvvfWWs72srMwkJCSY0aNHm4KCAvPqq6+a6Oho87vf/c6Z88knn5jw8HAzd+5cs337djN9+nTTqlUrs3XrVmfOnDlzTGxsrHnzzTfN5s2bzT/+4z+apKQkU15efs76PXTokGnfvr359a9/bXbu3GkKCgpMenq6SUhIMJWVldb1e9VVV5l77rknaE5ZWZnz+urqanPRRReZlJQU8/nnn5t33nnHdOzY0UybNs2Z89VXX5mYmBgzadIks337dvPss8+a8PBws3LlSmfOa6+9ZiIjI82LL75otm3bZu655x4TFxdniouLnTnjx4833bp1Mzk5OWbTpk1m8ODB5he/+MUp93qmel68eLH553/+Z7NmzRrz5Zdfmv/5n/8x0dHR5tlnnw3Jnk+33+ONHDnS+bn/9ttvm22/zek962T92vaedSo9r1u3zvh8PjN79mxTUFBgdu7caV5//XVz9OhRZx/XXnutufjii8369evNRx99ZHr27GlGjRrlbA+1nt1mZYD5voceesj89Kc/NbW1tc66zz//3PzkJz8xBw4caPAL/eDBgyY6Otq8//77P7jPhQsXmnbt2pmKigpn3dSpU02vXr2cr2+++WaTlpYW9LpBgwaZ3/zmN8YYY2pra01iYqJ5/PHHne2lpaXG6/WaV1999Zz1u3HjRiPJFBYWOuu2bNliJJkvvvjCun6vuuoq89BDD/3g/HfeeceEhYWZoqIiZ93zzz9vfD6f09+UKVNM3759g153yy23mNTUVOfryy67zGRkZDhf19TUmC5dupjZs2c7vbVq1cosX77cmbNjxw4jyeTm5ja5X2Ma3/OJ3H///Wbo0KHO16Hcc1P7XbhwobnqqqtMTk5OgwDTnPptbu9ZJ+vX9vcsYxr2PGjQIDN9+vQfnL99+3YjyWzcuNFZ9+677xqPx2P+9re/GWNCv+dzzcpTSMerrKzU73//e40dO9b50MbvvvtOt912mxYsWHDCz07Kzs5WbW2t/va3v6lPnz7q2rWrbr75Zu3bt8+Zk5ubqyFDhigyMtJZl5qaql27dunbb7915qSkpATtOzU1Vbm5uZKkPXv2qKioKGhObGysBg0a5Mw5F/326tVLHTp00OLFi1VZWany8nItXrxYffr0UY8ePazrV5JeeeUVdezYURdddJGmTZum7777ztmWm5urfv36BT30MDU1VYFAQNu2bTulXiorK5WXlxc0JywsTCkpKc6cvLw8VVVVBc3p3bu3unfv3uR+m9rziZSVlal9+/bO16Hac1P73b59u2bNmqWXX35ZYWEN38qaU7/N7T3rZP3a/J51op5LSkq0YcMGxcfH6xe/+IUSEhJ01VVX6eOPP3Zek5ubq7i4OF166aXOupSUFIWFhWnDhg0h37MbQvZJvKfqzTffVGlpqX7961876yZOnKhf/OIXGjly5Alf89VXX6m2tla//e1vNX/+fMXGxmr69On65S9/qS1btigyMlJFRUVKSkoKel39L8SioiK1a9dORUVFDZ4MnJCQoKKiImfe8a870Zxz0W/btm21Zs0aXX/99XrsscckSRdccIFWrVqliIgIp1Zb+r3tttt03nnnqUuXLtqyZYumTp2qXbt26Y9//KNTx4lqOL7GH5oTCARUXl6ub7/9VjU1NSecs3PnTmcfkZGRDT409HT6bWrP37du3Tq9/vrrysrKctaFas9N6beiokKjRo3S448/ru7du+urr75qsN/m1G9ze886Wb82v2edqOf6n89HHnlETzzxhC655BK9/PLLGjZsmAoKCnTBBReoqKhI8fHxQfuJiIhQ+/btg+oN1Z7dYH2AWbx4sUaMGOF87Paf/vQnrV69Wp9//vkPvqa2tlZVVVV65plnNHz4cEnSq6++qsTERH3wwQdKTU09J7U3RVP6LS8v17hx43T55Zfr1VdfVU1NjZ544gmlpaVp48aNio6OPlflN9r3+5Wke++91xn369dPnTt31rBhw/Tll1/qpz/9qRtlnlGn23NBQYFGjhypmTNnOj/foawp/U6bNk19+vTR7bff7kbJp6Up/Tan9yzp5P3a/J4lNey5trZWkvSb3/zG+Ty/n/3sZ8rJydGLL76o2bNnu1arzaw+hfSXv/xF77//vu6++25n3erVq/Xll18qLi5OERERTlpPT0/X1VdfLUnq3LmzJCk5Odl5XadOndSxY0cVFhZKkhITExvcaVD/df1pmh+ac/z24193ojnnot+lS5dq7969WrJkiX7+859r8ODBWrp0qfbs2aO33nrLqn5PZNCgQZKk3bt3n3YvPp9P0dHR6tixo8LDw0/ab2VlZYM7X5rar9T0nutt375dw4YN07333qvp06cHbQvFnpva7+rVq7V8+XLnZ37YsGGSpI4dO2rmzJnNrt/m9J51It/v19b3LOnEPZ/o30+S+vTpE/TvV1JSErS9urpaBw8ePGk/x/fiRs9usTrALFmyRPHx8UpLS3PWPfzww9qyZYvy8/OdRZLmzZunJUuWSJIuv/xySdKuXbuc1x08eFB///vfdd5550mS/H6/PvzwQ1VVVTlzsrOz1atXL7Vr186Zk5OTE1RTdna2/H6/JCkpKUmJiYlBcwKBgDZs2ODMORf9fvfddwoLCws6/1z/df1fBrb0eyL1Pde/Sfj9fm3dujXozSA7O1s+n895AzlZL5GRkRo4cGDQnNraWuXk5DhzBg4cqFatWgXN2bVrlwoLC5vU7+n0LEnbtm3T0KFDNWbMGP3nf/5ng9eEYs9N7fcPf/iDNm/e7PzMv/DCC5Kkjz76yLlttTn125zes06lX1vfs36o5x49eqhLly5B/36S9Oc//zno36+0tFR5eXnO9tWrV6u2ttYJeKHas2vcvoq4qWpqakz37t3N1KlTTzpXJ7iNeuTIkaZv377mk08+MVu3bjXXXXedSU5Odm7RKy0tNQkJCeaOO+4wBQUF5rXXXjMxMTENbleLiIgwTzzxhNmxY4eZOXPmCW9Xi4uLM2+99ZbZsmWLGTlyZJNuVzudfnfs2GG8Xq+57777zPbt201BQYG5/fbbTWxsrNm/f79V/e7evdvMmjXLbNq0yezZs8e89dZb5vzzzzdDhgxx5tTfRj18+HCTn59vVq5caTp16nTC26gnT55sduzYYRYsWHDCW2y9Xq/JzMw027dvN/fee6+Ji4sLurtp/Pjxpnv37mb16tVm06ZNxu/3G7/f36hez0TPW7duNZ06dTK333570K2cJSUlIdvz6fT7fR988MEP3kbdXPptLu9Zp9Kvje9ZP9azMcbMmzfP+Hw+s3z5cvPFF1+Y6dOnm6ioKLN7925nzrXXXmt+9rOfmQ0bNpiPP/7YXHDBBUG3UYdiz26yNsCsWrXKSDK7du066dwTBZiysjIzduxYExcXZ9q3b29uuOGGoFv2jDFm8+bN5oorrjBer9f85Cc/MXPmzGmw72XLlpkLL7zQREZGmr59+5qsrKyg7bW1tebf//3fTUJCgvF6vWbYsGGnVPOZ7ve9994zl19+uYmNjTXt2rUz11xzTYPbQG3ot7Cw0AwZMsS0b9/eeL1e07NnTzN58uQGz8zYu3evGTFihImOjjYdO3Y0//Iv/2KqqqqC5nzwwQfmkksuMZGRkeb88883S5YsaVDHs88+a7p3724iIyPNZZddZtavXx+0vby83Nx///2mXbt2JiYmxtxwww3mwIEDje73dHueOXOmkdRgOe+880K259P9N/5+X98PMM2t3+bynnWq/dr2nvVjPdebPXu26dq1q4mJiTF+v9989NFHQdu/+eYbM2rUKNOmTRvj8/nMXXfdZQ4dOhTSPbvJY4wx5/igDwAAwGmx+hoYAADQMhFgAACAdQgwAADAOgQYAABgHQIMAACwDgEGAABYhwADAACsQ4ABAADWIcAAAADrEGAAAIB1CDAAAMA6BBgAAGCd/w+4IwoXKjCk2QAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 10084\n",
      "working on HD 500 out of 10084\n",
      "working on HD 1000 out of 10084\n",
      "working on HD 1500 out of 10084\n",
      "working on HD 2000 out of 10084\n",
      "working on HD 2500 out of 10084\n",
      "working on HD 3000 out of 10084\n",
      "working on HD 3500 out of 10084\n",
      "working on HD 4000 out of 10084\n",
      "working on HD 4500 out of 10084\n",
      "working on HD 5000 out of 10084\n",
      "working on HD 5500 out of 10084\n",
      "working on HD 6000 out of 10084\n",
      "working on HD 6500 out of 10084\n",
      "working on HD 7000 out of 10084\n",
      "working on HD 7500 out of 10084\n",
      "working on HD 8000 out of 10084\n",
      "working on HD 8500 out of 10084\n",
      "working on HD 9000 out of 10084\n",
      "working on HD 9500 out of 10084\n",
      "working on HD 10000 out of 10084\n",
      "all done checking HD and complement contiguity for all 10084 HDs\n"
     ]
    }
   ],
   "source": [
    "patchedUse, unpUse = [0.]*nUnits, [0.]*nUnits\n",
    "patchUpHDunitList = [HDunitList[t].copy() for t in range(nHDs)]  #more safekeeping for later contig troubleshooting\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        patchedUse[u] += HDweight[t] * nDistricts\n",
    "    for u in unpatchedHDlist[t]:\n",
    "        unpUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(patchedUse,bins=50, label=\"patched\",histtype=\"step\")\n",
    "plt.hist(unpUse, bins=50, label=\"unpatched\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "patchedAvg, patchedSD = getWeightedAvgAndSD(patchedUse,unitPop)\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unpUse,unitPop)\n",
    "print(\"unpatched, patched use avgs are\",r5(unpatchedAvg), r5(patchedAvg),\"and their SDs are\",r5(unpatchedSD), r5(patchedSD) )\n",
    "print(\"And here is the pop distro\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP, ls=\"--\",color=\"orange\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%500 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs)  #these HDunitLists now appear to be sets\n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "1ee72cf0-618e-411f-aa37-518ac2c679ce",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets write these UNIT lists to a file\n"
     ]
    }
   ],
   "source": [
    "#optional intermediate save\n",
    "print(\"Lets write these UNIT lists to a file\")\n",
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"underPatched.csv\" #\"contigUnpatchedB.csv\"  #underPatched\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "77c07848-50c2-4fe9-8841-768b02bf4ac4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "default use threshold for moving on to next overused unit is 1.08\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated stopMaxUse value 1.02\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are currently 3208 units out of 9678 with usage above 1.02\n",
      "maxExchangePop is currently 0.05 fraction of avgDistrictPop\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter updated maxExchangePop fraction 0.05\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this block reduces overuse, with exchanges up to 37683\n",
      "current avg and SD of unit usage are 1.00097 0.05991 . Now trying to reduce up to 3208 units' overusage\n",
      "starting to reduce usage for unit 8581 with usage 1.2509 . Total units tried = 1\n",
      "try to drop unit 8581 from 43 th HD.  usage down to 1.1600275293486395\n",
      "try to drop unit 8581 from 86 th HD.  usage down to 1.1002300252222064\n",
      "all done trying to reduce usage of unit 8581 final usage = 1.01627 324 sec elapsed 100 4 successful, failed patches, couldn't start= 18\n",
      "current avg and SD of usage are 1.00093 0.05731\n",
      "starting to reduce usage for unit 1383 with usage 1.21356 . Total units tried = 2\n",
      "try to drop unit 1383 from 48 th HD.  usage down to 1.1132926512123316\n",
      "all done trying to reduce usage of unit 1383 final usage = 1.01983 596 sec elapsed 83 0 successful, failed patches, couldn't start= 8\n",
      "current avg and SD of usage are 1.0009 0.05521\n",
      "starting to reduce usage for unit 1661 with usage 1.2123 . Total units tried = 3\n",
      "try to drop unit 1661 from 41 th HD.  usage down to 1.1237228495779656\n",
      "try to drop unit 1661 from 82 th HD.  usage down to 1.0649178131245216\n",
      "all done trying to reduce usage of unit 1661 final usage = 1.01944 1366 sec elapsed 95 2 successful, failed patches, couldn't start= 15\n",
      "current avg and SD of usage are 1.00089 0.05331\n",
      "starting to reduce usage for unit 394 with usage 1.1735 . Total units tried = 4\n",
      "try to drop unit 394 from 50 th HD.  usage down to 1.0919837864686757\n",
      "all done trying to reduce usage of unit 394 final usage = 1.01394 1625 sec elapsed 67 0 successful, failed patches, couldn't start= 20\n",
      "current avg and SD of usage are 1.00088 0.05185\n",
      "starting to reduce usage for unit 6136 with usage 1.17078 . Total units tried = 5\n",
      "try to drop unit 6136 from 29 th HD.  usage down to 1.1131241440004582\n",
      "try to drop unit 6136 from 58 th HD.  usage down to 1.0647585937116335\n",
      "all done trying to reduce usage of unit 6136 final usage = 1.01982 1697 sec elapsed 81 0 successful, failed patches, couldn't start= 3\n",
      "current avg and SD of usage are 1.00087 0.05081\n",
      "starting to reduce usage for unit 1539 with usage 1.15131 . Total units tried = 6\n",
      "try to drop unit 1539 from 47 th HD.  usage down to 1.074425865724246\n",
      "all done trying to reduce usage of unit 1539 final usage = 1.01917 1752 sec elapsed 73 1 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00085 0.0499\n",
      "starting to reduce usage for unit 1346 with usage 1.14173 . Total units tried = 7\n",
      "try to drop unit 1346 from 42 th HD.  usage down to 1.108380732328051\n",
      "try to drop unit 1346 from 84 th HD.  usage down to 1.0813877345480682\n",
      "all done trying to reduce usage of unit 1346 final usage = 1.01658 1953 sec elapsed 58 0 successful, failed patches, couldn't start= 64\n",
      "current avg and SD of usage are 1.00084 0.04896\n",
      "starting to reduce usage for unit 1012 with usage 1.1298 . Total units tried = 8\n",
      "try to drop unit 1012 from 41 th HD.  usage down to 1.0709548825256976\n",
      "all done trying to reduce usage of unit 1012 final usage = 1.0182 2071 sec elapsed 47 0 successful, failed patches, couldn't start= 29\n",
      "current avg and SD of usage are 1.00083 0.04811\n",
      "starting to reduce usage for unit 7558 with usage 1.12875 . Total units tried = 9\n",
      "try to drop unit 7558 from 32 th HD.  usage down to 1.079402799202135\n",
      "try to drop unit 7558 from 64 th HD.  usage down to 1.0202156361580235\n",
      "all done trying to reduce usage of unit 7558 final usage = 1.01903 2106 sec elapsed 58 0 successful, failed patches, couldn't start= 6\n",
      "current avg and SD of usage are 1.00082 0.04748\n",
      "starting to reduce usage for unit 1275 with usage 1.12363 . Total units tried = 10\n",
      "try to drop unit 1275 from 38 th HD.  usage down to 1.0805903106558545\n",
      "try to drop unit 1275 from 76 th HD.  usage down to 1.028476470024491\n",
      "all done trying to reduce usage of unit 1275 final usage = 1.0188 2277 sec elapsed 65 0 successful, failed patches, couldn't start= 19\n",
      "current avg and SD of usage are 1.00082 0.04649\n",
      "starting to reduce usage for unit 2369 with usage 1.11649 . Total units tried = 11\n",
      "try to drop unit 2369 from 46 th HD.  usage down to 1.0607834157060965\n",
      "all done trying to reduce usage of unit 2369 final usage = 1.01995 2372 sec elapsed 76 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00081 0.04549\n",
      "starting to reduce usage for unit 8530 with usage 1.13038 . Total units tried = 12\n",
      "try to drop unit 8530 from 34 th HD.  usage down to 1.0459109957238424\n",
      "all done trying to reduce usage of unit 8530 final usage = 1.01855 2457 sec elapsed 42 1 successful, failed patches, couldn't start= 7\n",
      "current avg and SD of usage are 1.0008 0.04465\n",
      "starting to reduce usage for unit 250 with usage 1.10916 . Total units tried = 13\n",
      "try to drop unit 250 from 21 th HD.  usage down to 1.091691884211883\n",
      "try to drop unit 250 from 42 th HD.  usage down to 1.076290059682294\n",
      "try to drop unit 250 from 63 th HD.  usage down to 1.061292917826852\n",
      "try to drop unit 250 from 84 th HD.  usage down to 1.0409261012753994\n",
      "all done trying to reduce usage of unit 250 final usage = 1.01612 2597 sec elapsed 45 1 successful, failed patches, couldn't start= 52\n",
      "current avg and SD of usage are 1.0008 0.04396\n",
      "starting to reduce usage for unit 770 with usage 1.09802 . Total units tried = 14\n",
      "try to drop unit 770 from 41 th HD.  usage down to 1.030052742210956\n",
      "all done trying to reduce usage of unit 770 final usage = 1.01792 2639 sec elapsed 32 0 successful, failed patches, couldn't start= 16\n",
      "current avg and SD of usage are 1.00079 0.04344\n",
      "starting to reduce usage for unit 1278 with usage 1.10045 . Total units tried = 15\n",
      "try to drop unit 1278 from 44 th HD.  usage down to 1.0337625545287767\n",
      "all done trying to reduce usage of unit 1278 final usage = 1.019 2873 sec elapsed 39 2 successful, failed patches, couldn't start= 14\n",
      "current avg and SD of usage are 1.00079 0.04292\n",
      "starting to reduce usage for unit 3879 with usage 1.08879 . Total units tried = 16\n",
      "try to drop unit 3879 from 32 th HD.  usage down to 1.030429561487799\n",
      "all done trying to reduce usage of unit 3879 final usage = 1.01814 2895 sec elapsed 32 0 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 1.00078 0.0426\n",
      "starting to reduce usage for unit 1000 with usage 1.08821 . Total units tried = 17\n",
      "try to drop unit 1000 from 33 th HD.  usage down to 1.0200710118581033\n",
      "all done trying to reduce usage of unit 1000 final usage = 1.01761 2960 sec elapsed 26 0 successful, failed patches, couldn't start= 7\n",
      "current avg and SD of usage are 1.00078 0.04218\n",
      "starting to reduce usage for unit 596 with usage 1.08561 . Total units tried = 18\n",
      "try to drop unit 596 from 46 th HD.  usage down to 1.044974254845499\n",
      "all done trying to reduce usage of unit 596 final usage = 1.01782 3138 sec elapsed 68 0 successful, failed patches, couldn't start= 7\n",
      "current avg and SD of usage are 1.00078 0.0417\n",
      "starting to reduce usage for unit 2187 with usage 1.08422 . Total units tried = 19\n",
      "all done trying to reduce usage of unit 2187 final usage = 1.01898 3245 sec elapsed 28 0 successful, failed patches, couldn't start= 8\n",
      "current avg and SD of usage are 1.00077 0.04131\n",
      "starting to reduce usage for unit 8800 with usage 1.08478 . Total units tried = 20\n",
      "all done trying to reduce usage of unit 8800 final usage = 1.01898 3276 sec elapsed 29 1 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.00077 0.04095\n",
      "starting to reduce usage for unit 5599 with usage 1.08348 . Total units tried = 21\n",
      "try to drop unit 5599 from 13 th HD.  usage down to 1.0504686514146317\n",
      "all done trying to reduce usage of unit 5599 final usage = 1.01936 3292 sec elapsed 25 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00076 0.04054\n",
      "starting to reduce usage for unit 8448 with usage 1.08245 . Total units tried = 22\n",
      "try to drop unit 8448 from 33 th HD.  usage down to 1.032406535863426\n",
      "all done trying to reduce usage of unit 8448 final usage = 1.01873 3565 sec elapsed 31 0 successful, failed patches, couldn't start= 7\n",
      "current avg and SD of usage are 1.00075 0.04013\n",
      "starting to reduce usage for unit 6267 with usage 1.08137 . Total units tried = 23\n",
      "try to drop unit 6267 from 40 th HD.  usage down to 1.027627299822886\n",
      "all done trying to reduce usage of unit 6267 final usage = 1.0198 3589 sec elapsed 34 0 successful, failed patches, couldn't start= 12\n",
      "current avg and SD of usage are 1.00075 0.03988\n"
     ]
    }
   ],
   "source": [
    "#SECOND PATCHING BLOCK -- OVERUSERS.  applies a suppression of LONG STRINGS.  run second for most states except MA, WA\n",
    "maxSD = 0.04 #0.06  #0.08  #0.04\n",
    "maxSD = float(input(\"enter max std devn; e.g.\",maxSD))\n",
    "stopMaxUse = 1.+  0.5 * maxSD\n",
    "print(\"default use threshold for moving on to next overused unit is\",r5(stopMaxUse) )\n",
    "stopMaxUse = float(input(\"enter updated stopMaxUse value\"))\n",
    "nInPlay = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > stopMaxUse:\n",
    "        nInPlay +=1\n",
    "print(\"there are currently\",nInPlay,\"units out of\",nUnits,\"with usage above\",stopMaxUse)\n",
    "nBigUsers = 5\n",
    "maxExchangePop = 0.05*aDP\n",
    "print(\"maxExchangePop is currently\",r5(maxExchangePop/aDP),\"fraction of avgDistrictPop\")\n",
    "newMEPratio = float(input(\"Enter updated maxExchangePop fraction\"))\n",
    "maxExchangePop = newMEPratio*aDP \n",
    "print(\"this block reduces overuse, with exchanges up to\",int(maxExchangePop)) #1/25/24\n",
    "maxGap = 0.9 * np.median(unitPop) \n",
    "maxNtries = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > stopMaxUse:\n",
    "        maxNtries +=1\n",
    "#maxNtries = int(currSD * nUnits / nDistricts)   #try up to about 10% of the districts a unit is drawn into\n",
    "#maxNtries = 10 #overrirde\n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "attemptedBigUs = list()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to reduce up to\",maxNtries,\"units' overusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedBigUs) < maxNtries: \n",
    "    #each round, find the (5) most overused not-yet-tried units. Pick the unit w/ most overuse of it + 1-nbrs\n",
    "    idx = np.argsort(unitUse)\n",
    "    idxNo, nBigFound, bigUsers = 0,0,list()\n",
    "    while nBigFound < nBigUsers:\n",
    "        consideredBigU = idx[-idxNo-1]\n",
    "        if consideredBigU not in attemptedBigUs:\n",
    "            bigUsers.append(consideredBigU)\n",
    "            nBigFound +=1\n",
    "        idxNo +=1\n",
    "    OUUclusters = [ [b] + unitNbrs[b] for b in bigUsers ]\n",
    "    bigOverUse = [np.sum([(unitUse[j] - 1.) for j in OUUclusters[i] ]) for i in range(nBigUsers) ]\n",
    "    bigI = bigOverUse.index(np.max(bigOverUse))\n",
    "    OUU = bigUsers[ bigI ]  #pick the unit that centers cluster with most overuse\n",
    "    attemptedBigUs.append(OUU)  #so we don't try this unit again in a future loop\n",
    "    OUUc = OUUclusters[bigI]  #the list of this unit and ALL its neighbors (to be curated below ...)\n",
    "    print(\"starting to reduce usage for unit\",OUU,\"with usage\",r5(unitUse[OUU]),\". Total units tried =\",len(attemptedBigUs) )\n",
    "    for u in OUUc.copy():\n",
    "        if unitUse[u] < 1.:\n",
    "            OUUc.remove(u)  #...drop any underused neighbors of the primary OUU from the target sheddable cluster\n",
    "    OUU2nbrSet = set( unitNbrs[OUU])\n",
    "    for u in OUUc:\n",
    "        OUU2nbrSet = OUU2nbrSet.union(set(unitNbrs[u])) \n",
    "    for u in OUUc:\n",
    "        OUU2nbrSet = OUU2nbrSet.difference({u})\n",
    "    ouuHDs, ouuDists = list(), list()\n",
    "    for t in popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if OUU in HDunitList[t]:\n",
    "            HDadjoinSet = set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(OUU2nbrSet) ) > 0: #the OUU or one of its overused 1-neighbors adjoins the complement\n",
    "                ouuHDs.append(t)  #so we can shed the OOUc to the complement\n",
    "                ouuDists.append( unitCP[OUU].distance(hdCP[t]) / avgDist[t] )\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo, idx0 = 0, 0, 0, 0, np.argsort(ouuDists) #work from farthest HD in\n",
    "    while unitUse[OUU] > stopMaxUse and idxNo > -0.5*len(ouuHDs): #arbitrarily only examine 50% of HDs, biasing farthest ones\n",
    "        idxNo -=1\n",
    "        if idxNo % int(0.1*len(ouuHDs)) == 0:\n",
    "            print(\"try to drop unit\",OUU,\"from\",abs(idxNo),\"th HD.  usage down to\",unitUse[OUU] )\n",
    "        t = ouuHDs[idx0[idxNo]]\n",
    "        trySet = set(HDunitList[t]).difference(set(OUUc))\n",
    "        contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        if not (contig and complementContig):  #dropping the cluster creates a problem (likely an HD discontig).  Try something simpler ...\n",
    "            if len(set(unitNbrs[OUU]).intersection(HDadjoinSet) )  > 0:  #Yay! The OUU itself on border.  Try dropping just it, not the full cluster\n",
    "                HDouuSet = {OUU}\n",
    "                trySet = set(HDunitList[t]).difference( {OUU} )\n",
    "                contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        else:\n",
    "            HDouuSet = set(HDunitList[t]).intersection(set(OUUc))\n",
    "        if contig and complementContig:  #we can at least drop the cluster, let's go for more\n",
    "            #HDouuSet = set(HDunitList[t]).intersection(set(OUUc))  #the subset of the OUU cluster that's in this HD.  Defined above\n",
    "            HDouuCpop = np.sum([unitPop[u] for u in HDouuSet])\n",
    "            giveUpOnShedding = False            \n",
    "            shedCandidates, shedScores = list(), list()\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if HDouuCpop + unitPop[u] <= maxExchangePop:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward far, overused\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            while HDouuCpop < maxExchangePop and not giveUpOnShedding:\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                    if contig and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDouuCpop += unitPop[shedU]\n",
    "                        #print(\"shedding unit\",shedU,\"from HD\",t,\"total shed Pop now\", HDouuCpop)\n",
    "                        HDouuSet.add(shedU)\n",
    "                        trySet.remove(shedU)\n",
    "                        del shedScores[shedCandidates.index(shedU)]\n",
    "                        del shedCandidates[shedCandidates.index(shedU)]\n",
    "                        newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                        for u in newSheddables:\n",
    "                            if HDouuCpop + unitPop[u] <= maxExchangePop and u not in shedCandidates:\n",
    "                                shedCandidates.append(u)\n",
    "                                shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            shedSet = HDouuSet.copy()  #set(OUUc).intersection(set(HDunitList[t]))\n",
    "            trySet = set(HDunitList[t]).difference(shedSet) \n",
    "            gap = aDP - np.sum([unitPop[u] for u in trySet])\n",
    "            nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "            for u in trySet:\n",
    "                for uu in unitNbrs[u]:\n",
    "                    if uu not in HDunitList[t] and uu not in nearHDlist and unitPop[uu] < gap + maxGap and unitUse[uu] < 1.01:\n",
    "                        nearHDlist.append(uu)\n",
    "                        nearHDscore.append(5.*(unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                        #bias toward UNDERUSED, close\n",
    "            addedSet = set( )    \n",
    "            stillGoing = True \n",
    "            while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "                nearHDscore2 = nearHDscore.copy()\n",
    "                for ij, uu in enumerate(nearHDlist):\n",
    "                    nHDnbrs = len( set(unitNbrs[uu]).intersection(trySet) )\n",
    "                    if nHDnbrs == 1 :  #BIAS AGAINST CREATING A SLIM CHAIN\n",
    "                        nearHDscore2[ij] *= 0.5   #make this score closer to zero (less negative)  #NEW FOR GA 3/11/24\n",
    "                idx, ij, notYetPicked = np.argsort(nearHDscore2), 0, True   #originally, used nearHDscore itself here\n",
    "                while ij < len(nearHDscore) and notYetPicked:        \n",
    "                    listNo = idx[ij]   #nearHDscore.index(np.min(nearHDscore))\n",
    "                    unitNoToAdd = nearHDlist[listNo]  #add this unit ...                            \n",
    "                    canAdd  = wontEnclave(unitNoToAdd, list(trySet), unitNbrs, borderUnits)\n",
    "                    if canAdd:\n",
    "                        notYetPicked = False\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    stillGoing = False  #can't add any more units; we can't without creating an enclave\n",
    "                else:\n",
    "                    gap -= unitPop[unitNoToAdd]\n",
    "                    addedSet.add(unitNoToAdd)\n",
    "                    trySet.add( unitNoToAdd)\n",
    "                    for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                        if uu not in trySet and uu not in nearHDlist and unitPop[uu] < gap + maxGap and unitUse[uu] < 1.01:  \n",
    "                            nearHDlist.append(uu)\n",
    "                            nearHDscore.append(5.* (unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] ) \n",
    "                            #bias toward UNDERUSED, ~close\n",
    "                    del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "                    del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "                    for ijj, uu in enumerate(nearHDlist.copy()):\n",
    "                        if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                            del nearHDscore[nearHDlist.index(uu)]\n",
    "                            del nearHDlist[ nearHDlist.index(uu)]\n",
    "            currPop = np.sum([unitPop[u] for u in trySet])\n",
    "            legitSwap = False\n",
    "            if abs(currPop - aDP) <= 2.* maxGap: #giving ourselves a bit more margin after exchanges\n",
    "                contig,cContig, __, ___ = enclaveCheck(list(trySet), unitNbrs) \n",
    "                if contig and cContig:\n",
    "                    legitSwap = True\n",
    "            if legitSwap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addedSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t]    = currPop\n",
    "                nPatchSuccess +=1\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "        else:\n",
    "            nCouldntStart +=1\n",
    "            #print(\"Due to discontiguity, can't drop OUU cluster for HD, OUU\", t, OUU)\n",
    "    print(\"all done trying to reduce usage of unit\",OUU,\"final usage =\",r5(unitUse[OUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"successful, failed patches, couldn't start=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )\n",
    "            \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "92f90621-e7fc-4891-a5cd-69033c3c48e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#copy one of two above blocks and run again if needed (n/a for NC)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "cb60da52-ca13-45dd-8bf0-475213183a0d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "overused units\n"
     ]
    },
    {
     "data": {
      "image/png": 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38Y9//IPbb7+d2267jenTp/PS+Jc5dCCVJ/79f8QYDnEoZQ6PTFtNp2YxFFqicbvd7Nixg3HjxvHUU08xZcoU/vnPf1K3bl1cLhc33ngjffr0Yfjw4WRlZTFjxgz+8Y9/VPNZn1l5rt/yv01c0Mw6Hf3qhJPr9rAkKw8FlKQf0SYDTaxmbHJrRgQAh8PBrl27/M/37t1LSkoK+ZmZxCcm8mrKelJTU/nkk08AGHXZpXyUmMhL69YxbNgwFi5cyIyVK5k5cybBX39DaGgoE+5/gi5durD3h73+WylLvlvC5MmTub3V7dV1qjXeV199Veo2zI8//siPP/7of56ZlUF+UR4P/fuf8FpzVKN0jsTEMmHfMTzeowDcc889PPXUUwDMmzePq666itDQUGbMmMGUKVOYO3cuF110ETt27KBfv35Ve4JVQJIPUSuEHa+GWkIpRabbyzZHIbkeLzpNw6BpJIZYiTLJr4WoemvWrCnVrV8yS2Zgo0a81+lijuzdW2rmSXx8PDNnzmT06NG8/fbbNGzYkI8++oi+ffty4OtvQNP8dT7Gjh3L888/T3x8PBMmTKj1YzjO16hRoxg1ahRQOmlMSkpi7969fPfdd0RGRgIwNvNGDi6fwVPhGndGRTGzVx+e+3AioWGhbNu2jYULF/LNN98wc+ZMf6l7KJ76HB8fz9ChQ8tMy70QyG0XIY5z+xQb8wrI9njRwN9LEmbQ0zrESpBexo2Iqre7f39CunYl5ixWUi1xYNgwdLYwGk5468yNxXk51ViQIUOGMHXqVIYOHcq+ffv48d+P4rOa6LlvNJn7bKR/thXvYQeNGjbi6aefZujQoaX2nzt3Ln379mX79u20aNGiis7m/MhtFyHOgVGn0fGEheuguIck1+NlvT2fQl9xnm7RaVwSFoxZBrGKKuDatZusXbtxHz5ywtbSnxn//hky//cVhCZfUwXRBbalS5fyxBNPsG7dOpxOJ4B/LM2pLF68mBEjRrB7926UUtStW5dXXnmlVHKQmprKQw89xMyZM3G5XGiaRtOmTfnqq6/o1KlTqeNNnTrV/7Xb5yZ2ehyehEOEPteCey5/nyFNOpy0t7VPnz4X9DIRknwIcRqaphFuNNA1ItS/rdDr49djudwQc2GvOikCi89ZdPJvnGQQdXC3q7D1rd3Jx9KlS3n00UdJSUnB5XL5t69cufKUyceXX37JoEGDUEr5y6Gnp6czbNgw6tWrxz//+U9/yfsTKaXYvXs3EyZM4LPPPivz/RJGnZFZN84qtd9v2Q6C9Tou/tsHnwudJB9ClJNVr6NreAhzMnIx67SSyQd0iQiR3hBR4Vpv21rdIdQ4S5cu5Z///Cc7duzA5/Od1T5ffvkld9xxh/95yX5169YlPT2d6667rlQSczLDhw8vV5yapnFVZCj7C538nJ5D7ygbllpye1fGfAhRAVw+H7Mz7FxXN7y6QxGi1rvvvvv43//+h9vtPm27klswe/fupVmzZhV6m+OBBx4otd7LmXh8iq/TsmgfaiUxNKjC4qhK5bl+144US4hKZtLpMOukhogQgaBkOfuzXY7+ySefrPDxFeVdBM6g0xhUP4pQg57Zx3JZlp2H6yx7bWoiST6EqAC7CoqIt8p6MjXJ0qVLGTBgQJml0E9n8eLFdOzYEbPZTEJCQqnBhCVSU1MZPHgwUVFRWK1W2rZty5o1ayr+BMQp3XzzzYwcOZJvv/32rNpXdPXQpk2bnvMicI2tZq6pE0aSLYjfcxxMTc1gb4GzQuMLBOeVfLz88stomuaf75yVlcVDDz1Ey5YtsVqtNGrUiIcffti/lLQQF6pQvf6C/pRyIcrPz6d9+/Zn3TW+d+9e+vXrR48ePUhJSWHUqFEMHz6cOXPm+NtkZ2fTtWtXjEYjs2bNYsuWLbzxxhtERMjg5KqUnJzMuHHjSq00ezr5+fkV+vr33HPPeS8CF6zX0z3Sxl31o9ieX8TO/FMMOK6p1DlatWqVatKkiWrXrp0aOXKkUkqpjRs3qoEDB6qffvpJ7dq1Sy1YsEA1b95c3XjjjWd93NzcXAWo3Nzccw1NiCrn8fnU10cylc/nq+5QxDkA1PTp00/b5rHHHlMXXXRRqW233nqr6tu3r//5448/rq644orKCPGCsmTJEtW/f39Vr149BahOnTr5vz7Vz2HRokUqKSlJmUwmVb9+fdWoUSNlMplUs2bN1JQpU5RSSh06dEgNGjRIRUZGKrPZrMLCwhTF85JP+ih5rdO1OZdHampqhb5fhwqdanWOo0KPWRnKc/0+p54Ph8PBoEGD+PDDD0tl9ImJiXz//fcMGDCAZs2a0bNnT1588UV+/vlnPB7PubyUEDWCXtPoGWnjh6PZ0gNygVqxYgW9evUqta1v376sWLHC//ynn36iU6dO3HzzzdStW5ekpCQ+/PDDqg414OXn5xMREeFfpXXNmjXcddddp2xf0uuUkJBAXFwchw8f5sCBA9xxxx3+HqjvvvuOrl274na76dChAy6Xi7y8vNPG8emnn5KYmFih5xYcHFzhq882sJjYUXBh9XycU/Lx4IMP0q9fvzK/iCdTMur1VOVhnU4ndru91EOImijaZOC6uhH8mJ5zQRcHqq3S0tKIiYkptS0mJga73U5hYSEAe/bsYeLEiTRv3pw5c+Zw//338/DDDzNt2rTqCDlgJScnc/vtt3PNNX/VIrn88stP2X7SpEk0bNiQmTNnEhERQUJCAh07dmTq1Kk0b96cm266iccee4x69eqxcuVK0tPTSUxMZNy4caeNY/ny5ezdu7fCzgugVatWFXq8Et0iQvk+LatSjl0dyp18fPXVV6xbt46XXnrpjG0zMjJ44YUXuPfee0/Z5qWXXiIsLMz/iIuLK29IQgQMo07DotPhluSjVvL5fHTs2JHx48eTlJTEvffey4gRI5g0aVJ1hxZwSsZlnI0VK1YQGhpKfHw8VquVfv368a9//Quj0chbb71F37592b9/Px6PB4fDwdatW9m7dy9PPvnkaY+bnZ1NbGzsSQu1nahk/MapxnFER0f7v77nnnvO6pzKq4HFRITRQL7XWynHr2rlSj4OHjzIyJEj+fzzz7FYLKdta7fb6devH23atOE///nPKduNHTuW3Nxc/+PgwYPlCUmIgLLeXkCs2YhJio1dcGJjYzl69GipbUePHsVms2G1WgGoV68ebdq0KdWmdevWpRaEE+WXlpZGZmYmvXr18vdAxcTE4Ha7+f3334mJicHn87F27VqaNm2K1+vF4XCc8bgul4s9e/b8vVp9GSU9mafq0czIyACKf/7lLTRWHldGhPJ9WjbeC+DDTbn+Qq5du5b09HQ6duyIwWDAYDCwZMkS3nnnHQwGA97jGVleXh7XXHMNoaGhTJ8+HaPReMpjms1mbDZbqYcQNdGCTDuRRj2X1LIyybVF586dWbBgQalt8+bNo3Pnzv7nXbt2Zfv27aXa7Nixg8aNG1dJjBeyvLy8Mre9SraXrNsCsGHDhnOYaVIxF/Nnn32W+Ph4NE1D0zT0en2ZZKRhw4b+75/4OJu6IEadxs2xkbRdvolva/gtmHIlH1dffTUbN24kJSXF/+jUqRODBg0iJSUFvV6P3W6nT58+mEwmfvrppzP2kAhxoUh3uWlgNlV3GOIsORwO/98xKB7UmJKS4u+lGDt2rH8Q5Jblhwk62I4d23bRu8OtfPTCT/z3v//lm2++YfTo0f5jjh49mj/++IPx48eza9cuvvjiCyZPnsyDDz5Y5ed3IYmNjfV/uC3pgTp69ChBQcWVQNPT0/0JR8eOHalbt+4ZjxkTE4NSiutuuJHGjRszZMgQYmNjMeiM2IIiCTrJtatz584kJiZiNpv9QwS6d+9OvXr1gOLxkKmpqf72Pp+Pjz/+mBdffBEovs1zqmm97du3B6BJkyYnTU5K/g9Z9To+ToynfQ2tgup3vlNrunXr5p9qm5ubqy677DLVtm1btWvXLnXkyBH/w+PxnNXxZKqtqKkKPF717ZHM6g5DnKVFixaddJrkkCFDlFJKDRkyRHXr1k0ppdSO1WnqvX8uUA8PeEM1jEpQBp1RNW3a1D/F80Q///yzSkxMVGazWbVq1UpNnjy56k6qBip536dPn37KqbaPPfaYCgoKUiNHjlSPPfaYSkxMVLfffrtKTExUNptN3X777So2NlaZzWZ1zz33qNtvv11dccUVatSoUSo+Pl7Vr19fjRo1SnXu3PmkMTidTnV4T6bKOuJQhQ6n2pOSrn74/kt1883/UDfcMMAf48CBA0vt9+uvv6qnnnpK/fDDD2X+Dz311FP+5zabTSml1NChQxWgNE1T3bp1U8OHD1eACgsLUzt37lRKKZWenl7q2jlv3jwFqEWLFpV67S8OZ5z/m1/BynP9rtDk41S/zIDau3fvWR1Pkg9Rky3IkP+3FyKfz6eO7M5RB7dmqoPbslShw1XdIdVoeXl5av369Wr9+vX+a8QjjzyiAPXmm2+qu+++Ww0cOFA59+1Tj9x1lxrQrZsyGAwqKjxc/TJpkjIajErTNNUpKUm1bt1a6fV69fbbbytN01Tjxo3V999/r3Q6nTIajerKK69UCQkJKigoSH322WfnFO+pko+TtTGbzf5tl156qX+7UkpZLBYFKIvFokwmkzIYDApQdevWPeVxR44cqZo1a1amhtDmvAL1+p4j53Q+laVKk4+KJsmHqKk25RWoDfb86g5DiIB3ug+qJY+goCB1nc2mrrfZ1CVWq3ottp7SQOlARer1yqbTKUDFxsb6e6DeeOMNBSiDwaBiY2NVeHi4AlT9+vXPqweqPMlHo0aN/NtGjRrl3/7zzz+XOj9N00o9nzp1apljzp07V+n1eqXX60sVUysx+1iO+veyNSq497UqPDJSWSwWlZiYqFavXn3O53o+JPkQoopttOertbmBX4FQiEBxxtted96pLrFa1ZaWrfyPqXFxqpXZrIyapuqbjeo/d99S5rgVddvr71VYS3o1dMeTnieeeKJU+5I2JpPJX3k1MTHRv12v159VdVSz2aymTZum9uzZo8xms9I0TS1evFi9++67Sq/Xq9mzZ/tfc1daurLUq6963XaHWr7iD7Vnzx41Z84ctWvXrnM65/NVnuv3ySt/CSHK5bDTTZ/osOoOQ4gao3v37qctxjdl2jRc9w5EZe9H70yD7H0kFGRwS2E0R+vGEHfd2+ijW5TZr3///vTv3/+8Ylu6dCmPPvooW7ZsKTVlNzg4mOHDh/Pqq6+ecl+Xy0VcXBzx8fHMnz/fv91kMvmL0Z2MXq9n4cKFLF++nIYNGzJp0iQMBgO9e/emW7dudOvWjWXLlvnrmgB8+NYbNIlrxN1vvkOXelEAxMfHn9e5V5nKz4XKR3o+RE0z+1iOSiuSMQBCXChONZC05LYLf+v52LNnj7+NTqdT7777bpkejfT09FLPu3XrVuq50WgsFUPJeJEZM2b4t/3vf//zD15VSqnWrVurUaNGqauu+4eKrlNHdejQoVoHOFf62i5CiGIunw+zTiPGfOpaNkKImiU4OJi1a9eWqVa6fft23nvvPQAWL15MnTp1aNasWakKtj6fj1EjR5baLyEhgUsuuaTUtiVLlpR67na7CQoK8k/v3rVrFyEhIfTr18/f5lTl/Lu0ac3zX33HzfcMrzHl/OW2ixDnwaBpFHhlITkhLhQlt1w2bNhAUVHpxdw2b97MQw89BBQnB5mZmeTk5PDNN9+Uauf92+KSr776KsuWLWPSpEkUFBSc9HUfeOABcnNz+fTTTzGZTNjtdrp06XLKddGgONHp1KmTf7mTj1q0Zui2bUyaNIkhQ4aU+9yrkvR8CFEOWW4Pv2XlsSDTzoJMOwuz8rgiIrS6wxJCVJD8/Hx69+7NHXfccdp2sbGxhIeH4/F42Ldv32nbbtiwgWnTptHl2n6nbffZZ5/Rrl07vvjiCzweD02aNCn1/TOV80+ODiMjtmGNKOcvPR9CnIJPKfYUOtlf6PJvizDouSw8WNZuEaIGW7p0Ka+99hpr167lyJEjtGzZkj179uB2u0+7X3x8PKmpqf41YU7Vi/F3Jeubzf/u2zLfCwoKoqCgwF9evU2bNmzatInHHnuMX3/9tVTbM5Xzb2Ax4Tq4H0NMPZRS51BmvupoSgXWCjV2u52wsDByc3NlnRdR5Yq8Pv7IdeBRoAeaBplpZDEF9C+xEKJ8Zs2axfLly7n44osZOHAgERER2O12fwn36mY2m1m0aBFdunQ5bbsbb7yRH3/8keeee45bbrmFVatWMWLECN7870QMVyfTMthChNGA8fjfrxbBlbvcSXmu35J8CAHkuj2syMnHqtdxeXgwZunZEOKC8feejunTp3P99dcDoGkaN910E61atWLcuHHVG+gJ6tati9lsJicnh7y8PHQ6HS1atGDbtm1ceumlrFq1ikWLFuFwOBg7diw7d+4kPj6eMWPGMGLECKD4w1SW24MP2JRXyDV1KrccQHmu3/IXVtR6SikWZOXRN9pGt8hQSTyEOImlS5cyYMAA6tevj6ZpzJgx44z7LF68mI4dO2I2m0lISGDq1Kll2qSmpjJ48GCioqKwWq20bduWNWvWVGjs+fn5tG/fnvfff/+k3x80aBAvvPBChb7m+dDr9bhcLoYNG4bNZiM0NBSv14vFYsFgMHDZZZfRrFkzunXrRv/+/dm4cSNFRUVs3brVn3gAWPQ66ltMNLSYMOsCq/dWxnyIWs+tFCF6ndxaEeI0Si7gw4YNY+DAgWdsv3fvXvr168d9993H559/zoIFCxg+fDj16tXzF8nKzs6ma9eu9OjRg1mzZlGnTh127txJREREhcaenJxMcnJyhR1P07TTFkg7V3FxcRw8eBCv10tBQQGbN28mNTUVq9VKeHg4ubm56HQ6PvjgA5599tka/TdLkg9R6ymg0CfTZYU4nfJewCdNmkR8fDxvvPEGAK1bty5TofOVV14hLi6OKVOm+PerMRU6K8Hhw4f9X7tcLv9sl8LCQn9tj3bt2pGSksKmTZuqI8QKI/3Lolabm5HLihwH10hpdCEq1IoVK+jVq1epbX379mXFihX+5z/99BOdOnXi5ptvpm7duiQlJfHhhx9WdajlVllDJZOSkko9f/755wEICQnx33KpW7cuoaGh/Pzzz5USQ1WR5EPUWlsdhSQEWegeaZNxHkJUsLS0NGJiYkptO1WFzubNmzNnzhzuv//+GlOhs8TZ3PkwmUxnbGO1WjEa/6qUbDQasVqt6PV6IiIiKCoqwmw2M3/+fNq3b3/W03wDldx2EbXW7gIn/euGV3cYQlzQfE4PnvRC0MCTXbpiaEmFzvHjxwPFn/w3bdpU6RU6CwsLSUlJ8T9fuHAhGzZsOKdjnU0niMvlOmObK664gj/++AMAnU5HcHAwAA0bNuTQoUMAhIeHExoaisPhICgo6JziDRSSfIhaK0gvvR1CVKSsb3egGTT04RbqBEWSumUfR8avQjmL62fs3LAaW0joKSt0QvHYkO+//75S49y9e3epCqbvvvtupb7e2Vi+bDkFhcW9GT6fj7y8PMaPH8+9997LU089BRRPZU1ISGD9+vXcf//91RnueZPkQwghxHnzFbgpWHvU/7y9tRnzZ8/jiXsGEzX0IvQ2E7/1fYFLWnf0t/l7hU6AHTt20Lhx4wqNzeFwsGvXLv/z4OBg1q9fT2RkJHv27KFHjx4V+npnxRwMznz/05LEIzQ0lHfeeYfo6GjGjh3L1q1bgeLekLy8PDZt2sSdd97Jf//736qPuQJJ8iFqrYCqridEgPv7BXzv3r2kpKQQGRlJo0aNeOqFZ9j7x1Zev/wRDNFW/v3J80xr3443M7/lXuqwcMZCftmykG+e/9h/jNGjR9OlSxfGjx/vr9A5efJkJk+eXKGxr1mzplSCMWbMGACGDBnC1KlTiejQm4LMI4RfcQdHv3zyrI557aVhXOMO5vE/j1LoK+7ZibSGMeSOljRofZB3388ldX8RjZo0YcCAASxYsICdO3cSVrcBnjbXcmWHevz4ylP0fO5K+vuuJU85eWjUw6WmGffv378C34XAIhVORa2Q6/awo8BJnuev8sn1LUZaBVurMSohao7FixeftIeg5AI+dOhQdv+5nS/7vU6DF7qgaRqLFy9m9OjRbNmyhYYNG/Jw57u468Y7iLihuX//X3755ZQVOqtKgcvDsp0ZNK0TzPY0B1A8kLRkLKmmFdf2uLxpFGHW4kGhPp8bh2MrHk8hhuxwvBt0GKKsaB2drFzVB70WTLcr1qKdMIi0Oi3KtNMjqnKvqVJeXdR6+R4vv+c40B8fim4z6GkeZCbMKJ19QlSWgvXpZH29nfrPd0Fn0pf5/rGPNqILMhB1R+tqiK7q+HwulPKh11fuWirlsTDTTs8ASj7kL7G4oOzIL2J/oROjTuPqKBu6GlwBUIiaRhdS/Cn/yLg/TjoHVbm9WJpXbPXSQKTTnXlqbW0nyYcIaEopfODvwTiVLY5CDhS6aBpkprcUDBOiWpjjwwi/PgHlPnXFYHO89GgLST5EgHD6fKzNLcDp86EAH8X3W3WATtPwnXB3UB1/aCc8TwgyV/qKjUKI09MMOkIur1fdYYgaQJIPUe225Reyu8BJ98hQgvVl7xMLIYS4sEjyIarFEaeLTXnFJZYbWkz0qxNevQEJIYSoMpJ8iEqllMLh9eHweinw+jhU5Mbp8xFrNtIrylajl4QWQghxbiT5EH7Zbg9/5hXgVcVjLU4cV1GiZOSFdpLv/30cRkm7EIOeEL2OIL2Oy8ODZRE3IYSo5ST5uMC4fD6OON0cKHThVgoF1DUZaBFsKXXR9ynF7gInB4r+WvAo3KDnivBQDDrpjbgQLV26lNdee421a9dy5MgRpk+fzvXXX3/afRYvXsyYMWPYvHkzcXFx/N///R9Dhw4t1SY1NZXHH3+cWbNmUVBQQEJCAlOmTKFTp06VdzJCiBpNko8aTCnF7zkOCn2KkrTCpNOINRu5LDwY0/Fk46jTzaqcfNzHZ4yU9FA0CzLTMzJUbn3UEvn5+bRv355hw4YxcODAM7bfu3cv/fr147777uPzzz9nwYIFDB8+nHr16tG3b18AsrOz6dq1Kz169GDWrFnUqVOHnTt3lioRLYQQfyfJRw22v8hFtMlIy+DTV9GLMRuJMQdGiV9RfZKTk0lOTj7r9pMmTSI+Pp433ngDKF5tdNmyZbz11lv+5OOVV14hLi6OKVOm+PeLj4+v2MCFEBccufleQ3l8ipU5+bQIMld3KOICtWLFCnr16lVqW9++fVmxYoX/+U8//USnTp24+eabqVu3LklJSXz44YdVHaoQF5SlS5cyYMAA6tevj6ZpzJgx44z7LF68mI4dO2I2m0lISGDq1Kll2qSmpjJ48GCioqKwWq20bduWNWvWVPwJnAVJPmqgfK+Xn47lcF3dcLllIipNWloaMTExpbbFxMRgt9spLCyeJr1nzx4mTpxI8+bNmTNnDvfffz8PP/ww06ZNq46QhbgglNwiff/998+qfckt0h49epCSksKoUaMYPnw4c+bM8bfJyym+RWo0Gpk1axZbtmzhjTfeqLZbpHLbpQZamZPPgDrhGGVgqKhmPp+PTp06MX78eACSkpLYtGkTkyZNYsiQIdUcnRA1U2XcIv3qnQkBdYtUej5qKEk8REVyZBeRtie31MOgNzHxvx8QG1MPTdP438TP2b5hL6EhoeSkOknbm0u9evVo06aN/ziLFy9mxowZ/PHHHzWi61eI06mu2x8nvi7AypUrT/uaK1asoFWrVqVeNzg4uNQt0m//+x7Lli1D07RSjwcffPDs3owKJj0fQgi+f3UtjmxnqW1mZxQHMw5x+1Vj+HDus/wxYzfr9iyhYXgrfnh9HQBtW3Zk+/btwF9dv61atSIyMpLhw4fL7BhR4yxdupQHHniArVu34vOVXiDvtttuw+l0lpmmvnjxYgYPHkxqamqp9rt37+buu+9m+PDheL3eU77mpk2buOSSS0hMTGTKlCnlnpl28OBB/vjjDx566CH/zLSRI0fi8/koLCzEarWi0+kwmM3ce++9DBgwgF9//ZUJEyYQGhpavjeooqgAk5ubqwCVm5tb3aEEHLfXp+Zn5KrtjsLqDkXUQHl5eWr9+vVq/fr1ClBvvvmmWr9+vdq/f7/6YORiNfiGf6pbbrxdZaTmqYzUPLV2xUYVZA1SD90/SgHqrkF3K71er779YobKPOxQ/71/ofpy0s/KYDCoF198UY0YMUI1bNhQBQUFqc8++0wppdStt96q+vbt64/h8ccfV1dccUV1vQVqyZIlqn///qpevXoKUNOnTz/jPosWLVJJSUnKZDKpZs2aqSlTppRpc+jQITVo0CAVGRmpLBaLSkxMVKtXr674ExBlnM3P9O9tXnjhBdW8eXOl0+mUXq/377dkyRLVqlUrpWlayfqVJ30YDAZlMBhO2+bER8lrnO4RFham3n33XbVr165SsQPqiSeeOO17EBERoerWrVtq25VXXqkAVVBQoJRSymA0qs6dO/u/P3LkSBUWFqYuv/zyc3znyyrP9Vtuu9QQ2W4PPx/LoUt4CC3OMLVWiJNZs2YNSUlJJCUlATBmzBiSkpJ45plnUF5Fbn4mRzMOE1U/hKj6IXS8PJGZv87ktxWLAZgz/1c++ugjbrr9H0TWCwYNElt1YPr06Xz55Zd89NFH5OfnM2HCBAYNGgQE3uyYyhjIV9KbEygD+Wqbs/mZ/r3NuHHjSExMZMSIEdx9990ArF+/3t+uY8eOp33NN998kxdeeAGdTofuLCo2n9jrYbGc/O+3wWCgYcOGNGvW7IzHO9nxS27RlEhISADAarUCEBkT679F6nK5+Oyzz+jWrRsHDhwo9+tViApLeSqI9HyUlev2qBlHs5TP56vuUMQF6r8PLFQbFh085fc5ySfKv+/TvHlzNX78+FJtZs6cWerTl9lsVmazWY0dO1atW7dOffDBB8pisaipU6dW3MmcpZOd09899thj6qKLLiq17WS9OW3btpUelQBwNu89oOLi4spss9lsKioq6qx6Mp544gm1aNEiZTabz7r342wedevWLfPzLXm904mIiFAxMTFKeT1KeVxKuQpVtyuvKP7dy0pTqiBb9bxhoL/X8euvv1Z6vV4NHz68VG/I+ZKejwvI9vwi1uTmc10dmVYrKo/Pq/C4fWdueKJz+O/o8/no2LEj48ePJykpiXvvvZcRI0YwadKk8h+sCpxtrZNmzZqxa9cu8vPzAZg7d+5pjys9KtVj6dKlAKSnp5cZQFpQUMD9998PcMa/tTk5OfTr1w+zuWLqLOn1esLCwsjJyWHRokU4HA5SUlJISUkB4OjRo6RMHM6BL0bDxu8Ye8/13JV8Ocx6An4ZQ5jeRdaxozx2ZRDbRkbw3+sj+G3ZsuKDv94cXmnMTW0c/PHHH4wfP553332Xdu3a8cUXX8iAU3FyOsDp85Hu8kiVUlEplK+47P7v3+9i/bziLlj/n94T/gYv/GQLOSuicRXuJT9jFj6fjyWfGPj9a33xcRy5zP/yUyIPbPPv8/u2XVhMRj5+YCgd+vYvMzsGiqcFfv/995V2fufjTLVOrFYre/bsYc+ePYwZM4abb76Zjh07MmnSJL744gtyc3NPuobO36dGHj16lNDQUJKTk2natCn/93//x7Zt20pNjUxNTeWTTz6RNXTOQ0lyeNlll/kTkRIej4cnn3yScePGoZQ62e5+ixYtIj4+nv3791dIXF6vl9zcXHr16sUPP/zAJZdcQo8ePfzfnzJlClOmwJD2RqZe/z+OrC3kQI4PttohKIq4CCMXN4phXoaJtycfoWFMJEP/0Znv5v+B9fapsHshrfbvYvr06fz73/9m+/btNGzYsNQt0qomyUeAax5soXmwhXX2fNbbC0gMtdLQYqrusMSFRINWnWPRG/WEhJs46d/dVyGudRRtOjdg9YyP8XntNGqXTJ1GoZgsxcnHZYezWLE+hbY9+/p3+37jTtq3bo2zIJ/U7Zvp2rWrf3ZMiR07dtC4cePKPMNK9fdaJwDNmjVDp9ORm5t70n1O7FEp6QW54oor+P333/29IA0aNGDgwIHcfPPNLF68mNzcXC655BKZJXQWlFKkOlIx6AyY9CZ8yodSio5XFY/liK4XDUBGYQYH7H+Nedh2vKfhTPbt28d9993HxIkTKzTuFStWEBYWRvfu3f0JkKZpTJ8+ne7bniLfGMmfLe9gVCcNBazVDKAU8W2/Y/naTXz1ztji/ZTi/96cQpuExqzecZA6GVkoFP3792fNmjV88MEH7N27F4Oh+lIAST5qiI62YABS7AVszCugd1SYrD4rKoSmaVw9pE2Z7Q6Hg127dvmfG6ILMDXMxVqvLkV5x1jnOETqvOJP4wD1OnUhMTGRGatTGDZsGAsXLmThH6uYOXMmnu0bcGRnMnr0aLp06cL48eO55ZZbWLVqFZMnT2by5MlVdr6ntGcJ2A+X2hQbomfdwhkMmP0ta7fs5UhGDv+6rQ+2ECvW7dPBFHzK3pxff/0VgBtvvBGfz1eqB2TFihX89ttvvP322/59Sm7VfPTRRyilOHDgAO+99x6PPvooISEhLFu2jBUrVnDZZZeVCf2BBx4460G0tYHT6yT5h1MX6Zq3bR4AL6x4gbddxT8DzaRx1457ATDo9Hh8p54a63Q6iYmJwePxVGDUxT0z9erVK/O7t3fvXtJ2B3FtSArt8zYwdn4RqXmKT24oHkz6n4Y+En928M0roxiWZGThXi8LlhUx844gLtnwDAC/h1+Dz+djypQpDBkypFoTD0AGnNZEhR6v+iU9W+3Mlym3ovIsWrTopIPi+vXsod4ZcpMaMmSI6tatW5l9OnTooEwmk2ratKl/EOXMd15TXz37uFJKqZ9//lklJiYqs9msWrVqpSZPnlzFZ1aMEwcnFuYo9aytzOOxLibVOExTT11pUj/cYlWAurKRXvVtpve3uf365FLThwGl0+lUZGSkAlSvXr0UoJ555hl/m6ZNm6qxY8eqI0eOqMsuu0zdcMMN/vf3oYceUuPGjfM/nz17tmrdurUaNWqUio+PVwaDQSUmJqrXXntNzZs3TwFq0aJFVfvmBaiSn6nP51OJUxPV0FlD1YL9C9SiA4vUkoNL1NKDSxWgYhrEKEC9+vGratWRVQpQLRNbqp6Tr1KAigyPOOPg0NDQ0AobaHriVNyEhIRT/u617Nxb5WSlqztuv1Vd0bWLysvNVA57tsrPy1Gzf52p2rdrp0wmk4qPj1cffThZuV1O5XG71cRFO1SLCQvUnDlzFKC2b99eKe9/ea7f0vNRA1n0OvrVCWdjXgGzjuXQxGpGAS6fwqzTaGQ1EazXV3eYooY7sev3RGtnzmD5158x9ZOpJ91n/fr1ZbYrpfzjR/r370///v0rOtyzcrJPlCkpKUTqC2kEjP2zMakh7fhkavE4i/sG7+W99km4Lr2P1ncPhW/asfyQ4teff4KOjWDSFYwedjNdBt7r782B4vN95513GDx4MA8++CDz58/n559/5rnnngOgQYMGFBQUEBsbS1ZWFnq9HqvVitPp5J133vH3mjRp0oS33nrLv4ZO9+7dcTgcPPTQQ4wcOZIrr7ySZs2a0a1btyp9HwPJyX6mf/75J6H5oVwaeynzJs5j//79PPbYY/422ceyAdizeg/Zu4q/9hZ5ce1xA5CVk33G183Ly6uwcyiZihsSEkJBQcFJf/cGffQHy3dlMvB/m0lvfjfmNjqSJ6UQbDJQJ9RMYoOmXPufz+jrVXy95iAv7IIXnp6HTgOfAm+UmT59+pxxPEtVkeSjBmsbGkTrYCtHXW4MmoZB03D6fKy3F5Dj9nJ1lA2rXiY0iYqlaRoel4vvXnz6tG1OtO/PdTRsk1jZoZ3RmjVrSg3kGzNmDABD7hzE1KZwxBfJgYOHQF88uDs+oQUzZ85k9OjRvP3uewA8+OCD9L22H2QUX/Auaduc6dOnM3bsWJ5//nkAEhMTGTRoEIMHD2ZTXvEifFu2bWNRph1Ng4YdLuanuXMZmJVHgdfL2vXr0TSNOvUbsDw7jyNFxRdBg8HAihUr/ONKWrdujd1u59577+XPP/9k8uTJPPfcc7V6JtypfqZxPeKwd7Jz5MgRtmzZ4q9vA8V1LoBSs6x27drFrpf/SmLOiqZx8kFS5+aKK6445TihixtHsj+zgM7NooiLCMLl8VHg9rLxUC6r92Xx286Mk+53fDw5l8YH1vggST5qOINOo8HfBqDWt5jw+BQLsuzUMxtpFxpUTdGJC1Hjdkm0uLwrynf2U3NbXNaVZp3KjlWoaqfqzcHrhheimfrcvdDhjjL7lPTmaJpGz549i7+hN/j37d69O59++ilQvLheXFycf5rk6/vSAHAWFnLb6i1oZgvey3uR8eEkkh94iKKCInzHVwnmqqu5MWU3hX+kYA4KYu/evXi9XmJjYzGbzaXGxzidTjweD0OHDq24N6gGOtXPdPCvg8lz5Z10bRX4ayDn9ddf7+89efybMcx9aRG9e/dm3rx5Z3xtHRo+Kib56N69O0uXLj3l+KcxvVswpneLcz7+okz7Oe9bGTQVKH0wx9ntdsLCwsjNzcVms1V3ODXeVkchh51uekaG1upPR0KcllLwXDj0GQdtbyn+RHv8PtHS5St47e33Wbv+T46kHeWJR0by0gvPgv0ITOyM57ZPWHxIT+/eA874MvP2bcVjslCks7Hspx+Z9OgY8nNzANB0OoLDIyjIs6MMRoyx9bn3tpt576WX0Ol0KKVOepGVwaYnd//8+1l7dC1Rlij/Nk+hh4K0AgB+f/R3Wg1tRVRiFI5UB3++9Wf5X+QMPR8a+FMTnU7nXytG0zT/z7KkSmpCQgJjxoxhxIgR5Y/jLCzKtNMjqnKvqeW5fkvyUQvYPV4WZdnpHBZCXakVIsTJvVgf3PllNs/a6Wb5QS8X19Mz8JtCnuhq4qVef5XIXp9oIyvyr97H++87xO7dLho1MrJvn/uvAxmMxMxdRd6H7+A9kop760aMLS/CuXQB6HXg9aKr1xBLr2QKPvsINI2ggXfgmvUdE16NZOTDR3j00ce57rrrWLBgAU8/XXzba9GiRXTv3r3S3paaan36epYcXFJq2641u3j/vrKJ2iX9L6FgeG/2v/0TtmOKq4c8yqePDi3Tzmg1ceXDN3BkwwFyj9rxvv4ZzY+No8W7+5mxfjNZ+cU9WKG2MJ67py+j/zkUWv416+aXX35h7Nix7Ny5k/j4+EpNNv5Oko8zkOSj8sw+lss1dcKqOwwhAlPaJsg9dPyJOv6JtvS/2kX/4InhA3lp1J243Fls3fkMposGERXdEzTQ0OjadTg7dx4sc3i9Qc+3Oxbz0n13sCkln/qNm9Oy6xUs+/xTml96Oetnz8Tn8xEd14hrHh7NkeVLWLTkNxokRDPtFT1bNjdl0qS97Ny5k9DQUOx2O3FxcezcuVN6NSvAkzsOsSQrj48Sm+BVCi/g9Sk8JV8rhVdR/FwpMlwexmw/yGftmtIx7yhHt26jTmI7ouMCs2ZNoCUfMuZDCCEAYhOLH38ze/Zsxo8fz9atWwFYtSeHFHcTgoPjyIgy89MHB8nO/txf7yQ8PBa9/jCRkZFkZ2f7a0HoNB2Ns62MGqox+M4cdqevZPfqlQCsnflT8Yvpdeg6X8qaOiGk5eXiy8pgwD2jCA5eydW92vPggz/h8/lo0qQJ+fn5DBs2TBKPCmIz6Nld6KTH6u1nbnycBoQb9EQ2aU5kk+aVF9wF6LySj5dffpmxY8cycuRIJkyYAMDkyZP54osvWLduHXl5eWRnZxMeHl4BoYrzJTXJhCi/P//8k99++83/fOHChSQlJTH4zlsZOhSOHs0kLc3p//6xY8cAcLvdpYpQud1uLr64E336hKDTgddXPF7giv+7n1UTpuFyFND86i5kr1/Dzh+mY7aFADDmhkEc3bUQvb640OD8+fM5ePAger2+1g82rUgPN46hZ2Qoek07/gDD377WaRqGkq/RsOg0gg1S1uBcnPM8zNWrV/PBBx/Qrl27UtsLCgq45pprePLJJ887OFGxTLriqbhC1FZLly5lwIAB1K9fv8zCYqdy2WWX0bx581JLp0+fPp2PPyoeO/D773+yZMkSNE1D0zT27duH1+vFbDb7q0jqj9fdKSgo4LHH66IpMJuKx4ksGzcRl6N4EOTOucvI2rWfJo0ac++dQwGoHxKD1+ugR/fX0DSNvn2Ly9d7vV4aNGhQbQuDXWiC9DouDQ/h4rBgOtiCiksZhFhpEWyhWZCFxlYzcRYT9cwm6piMRJkMknich3NKPhwOB4MGDeLDDz8ss7bAqFGjeOKJJ7j88ssrJEBRcTwKzDqp+yFqr/z8fNq3b3/Ws0NK1l1JTEwsNTCweOqtxuKDXUl+5C4e/O8E7n9vAv98dwKG40lF+rFjNEy8CABTSHEvxsCxTzJt861YbUHUb9eBG8a/zoDnXz4+u6ZYu1uHYGl3GRPefhud0cR1737Fs7/dxZtTn+fIkSOsWrUKTdP8BctuvvnminhrhKhS53Tb5cEHH6Rfv3706tWLcePGnVcATqcTp/OvLku7PbDmIl9IfIE1tliIKpecnExy8qnX/Pi7SZMmERMTg9vt5qeffvJv//nnnxn56GN8uvVWAOoE5aDTFHpN4fUW9y4qTcf+jZsBcLuKb7+s+nUuoQNfxZH3JnmrV7L3+JiPEpqmo80VnTHoNPYtmY3H5aJJpGLeriY4rQ2JjY31x5SRkVErqpu6PD7mbE6jwOXB41N4T3iUPPd4FV6fr/i5Uni9ihibhRFXNa3u8MUplDv5+Oqrr1i3bh2rV6+ukABeeuklfwYvKs+y7DxaBlvO3FAI4bdixQratGlDTEwM//73v3nkkUcA2Lp1KwcOFi9C1zlzDsbDOXzyySe4XC4szwwBIDLMxrPPPsvIkSPxFBZP4XUdKV5BtUWnbuz4Yx6PP/44CxcuJCUlBZfLRYMG9Xm655UsXLiQT7OzsVqtvH3XXbR5Zg5hIXX8C4MNHjyYKVOmMGbMmAt+wOmqvVk89GVxkTedBgadDr1O8z8MJ/6r1zDodBS6vKTZi7j10jhsFikvEIjKlXwcPHiQkSNHMm/ePCyWirmQjR071l8OF/BPHxMVK8ft5YoIc3WHIUSNkpaWRsuWLfnoo49KbS8qKmLcf56F+EFkZRzFmX0UgBkzZviLR2VlZTFy5MhS+zkcDiLcTkxmCxdddBHTp09n+/a/ZlfYbDbat29Pw4YN/QP5s3IdAFiNeubPn8+BAwdo0KABOTk5tWLAqcVYfKt47uiraBETelb7LNqezt1TVpPv9EjyEaDKNQBg7dq1pKen07FjRwwGAwaDgSVLlvDOO+9gMBj8i+OUh9lsxmazlXqIiiczXYQ4N02bNj1pddFX3y5e62Xsy++yePFiAD7++GMsFgs6nY7x48f79/n7gNV/jHyRjRs3cttttxETEwNAdHQ0mzdvxul0snv3bnr37g1Aoav476rFqPMvDDZr1iySk5OpX79+pZ57IAg9njzkFZ398vUh5uLP1fnOil3yXlScciUfV199NRs3biQlJcX/6NSpE4MGDSIlJcU/olsElgKvD8MF3jUrxPlauXIlK1asYPfu3ezZs4e9e/cSHh7O4sWLueyyy4iK+qtMt9lsZv2adQD836iRXNvnWn74bAbz58/HYrbi8/l47j/PYTQWXzh37tyJz+fDYglCZzQz4e5u/kGjR48W95pkZGQwMLkby374L7999x5Lf/mcYKuF7fP/R7JuJVZD8e/w/v37mT9/PsOHD6+y9+ZcZgktXryYjh07YjabSUhIOOkaK6mpqQwePJioqCisVitt27ZlzZo1pdqEWooTibwid5n9TyXIVHwtcjjL/4FYVI1y3XYJDQ0lMbF0EZ7g4GCioqL829PS0khLS/Mvcbxx40ZCQ0Np1KgRkZGRFRS2OBtun2KNPZ+jTjcD6oZXdzhCBLRZs2aV2WY0Glm+fDn5+aXLrjudTp566glIfo6UQ8fw5B7l90nfoFnDsPsMgIbT7S41iwWAmBZoSjH1+ua48zZw+/eF1A+BNAf4gIdj1nDFhhQAJv5WwBX1Ff33jqO/CTI9/YBopkyZQt26denXr1+lvA8nUzJLaNiwYQwcOPCM7UtmCd133318/vnnLFiwgOHDh1OvXj3/VOHs7Gy6du1Kjx49mDVrFnXq1GHnzp1lZlDarMUJnF16Pi4oFV7hdNKkSaUGkF511VUATJkypVbcn6xuuwuK2FvoQkdx9b1OYcF0Dg+p7rCECAglq5eW2Lt3LykpKURGRhIVFcXs2bMJDQ1l4sSJKKW47rrruPLKK7n33nvp3Lkzd999NwCDBw+m58XdmL/3d2I6t+b3ZUdY98c3XN68BRv278NlNOD1+WjTKI4Ne/dhMRopcrvpF2vg4v0fMzs1m/wGA9j85xNc1L4jjeIacvBQKjMjRxB741AWLl7CN1sfYeZPM+CSFvD+JUQZXP4Bp0OGDPHXEKkK5zJLKD4+njfeeAOA1q1bs2zZMt566y1/8vHKK68QFxfHlClT/PvFx8eXOVawSY9OK1/PR7AkH4FPBZjc3FwFqNzc3OoOpUZxeDzql/RstdVRUN2hCBGwFi1adHyhltKPIUOGqGnTpqlu3bqpbt26ldknISHhpPu1b99evTz8X6p5TLQC1Ot33KIig4OV1Wg8afvrevdVr9/ST93QrZPq1q2bGjx4sAJUeHi4uueee1SHDh2UyWRSTZs2VVOmTCkOIPewUs/alNo+R82ZM0cBavv27ef1PixZskT1799f1atXTwFq+vTpZ/XeJSUlKUDFxsb+Fd9xjRs3Puk5P/DAA0oppf73v/8pm83mb9+6dWs1atQoddNNN6k6deqoDh06qMmTJ5/0tdv9Z46auHjXWZ9focujGj/+i/ph3cGz3udCtzCj8q+p5bl+S8WpGu5gkYu5GbmstxfQO8pGq2BrdYckRMDq3r27f/DoiY+pU6ei1+v55z//6R88WqJTp058++23xwuLwd1338369evZsH4z119/Pb/t3ovNYub1W/qBJx+lfDg9Hrq3bMpj13Tjho4XUXLzpXNo8VeP334XCxcuZOnSpVx33XXk5eXx/PPPs379ev+AU39PsfH4zEJPoX/AaYsWLc7rfTjXYms9evQAYMCAAQwfPpw5c+b426xevZojR45w5MgR4uPjufbaa4Hi8gyaprFnzx7sdjuFhcUrv+7Zs4eJEyfSvHlz5syZw/3338+//vUvGjduXGacSKjFgL3QTZMmTfyVZE98/L3Kq9lQPB1XxnwEsEpNg86B9HycvTU5DvVHdl51hyHEBeHLL79Un376aZntp+otGXTHYDV06FAVHVVHGQ3FPR1vj3tLNW7YWN3Uf6Bq1byVMhqNKq5BQzXktjsVoFbPXq4euvY/qnWTJspgMChANU9oqvon91XKkaFU3lHVuFHDk/cg3NK7TGzl6cEoaRsVFaUApdfrVVBQkP/4nTp18h/nVI/g4GD/vlar9bRtT/W49957lVJKGY1G1bFjRzVo0CAVGRmpzGazAlRUVJTasmWLevfdd5Ver1ezZ89W10xYqv5v+kaVnp6ujhw54n/MmzdPAWrRokVlzrfts7PL1VtyoQu0ng9Z1baGcfp8rMzJp8jno2Vw8XoDQojzZzQa2b59Oy+++KL/EzWApmm8/PLLaJrG448/zl133UXbtm3R0Fi3fh19W15Bl7oX8+CM/8O4Np86hBF8RMfP138AFF9xv9/4KyGmYPK+P8hH817mtvYt+f7aY3y7Rc+zi/dwR/1D8FpxNc7Vt/jwqr/GaW1K99H70wJu7tO5TMzlGQian59P48aNmTt3LgAjRoxg7969/t6LJk2a8OSTTzJw4ED+97//cdFFF9G9e3euvfZavv/+e6Kjo8nIyADgpptu4rvvvgPgtQeuw5Wfw9Of/sYTt3Zl/JfLaBoOe3KgRbSBHRmlx13cfvvtAMTExLBjxw7atWvHrFmz+Pjjj/nuu+/Q6/W0bt261DiRsBuexV7kpk6dOqWO9fLLL5+yymuI2SBjPgKYJB81RL7Xy9KsPKx6HZeFhWDVyx0zISpSt27daNCgQamaHupvt2eguGZHp06dim9/ZNehRXwcvvoRMOP/8NYJokObjizdtAxfQgRoxRNeli/ZQFKLDnx5aA5xYfV485EXCG9ThG/it1hWzOB3Txu49QXQdNTR6UHTF++o0/PyC+/TrPEfdBvyf2ViLs9A0OTkZBYvXkzz5s3ZvHkzffv25frrr/cnWYMGDeL6668HICIigu+//56mTZvSsGFDjEYjrVu35s8//8Rut7Nv3z4aNGjAgQMHmDN7JvPuDGZDaz2f/bqcZhHFq/UCXHlpEt7Vm9h9rBCLAVxe6PbHENjehNDQUOx2u3/A6b///W8aNWqE1frXreO+ffsyatQobr7dWKbOh8vl4rPPPjtllddgswGHJB8BS5KPGmJJVh7XRIehk3odQlSK6OhooqOjy2z/+wyZ4OBgwsPDiYyMRL/EzJs7v+DYgeI1qRomx9Ov/fV8kZjIR7s+ZdiwYSxcuJBZa+cyc+ZMXnzxRa5s2gl9gyR8ifWZ8uu/6dGzF8uXL4fW/cu8tsvl4rOfbyq+wBrOv1LnihUr6NWrF5s3bz6rtj169OCzzz4jNDSU3bt307p1a1auXMm+ffto1aoVBw4cYFWql7HZt7EveD0H7WsY9/QTvDLhfcDOF4s28c9//pMJEyZQ5AGjXodmqw9HUigqjCAvL4+2bdty+PBh7HY7SimmTZvmjyEmJga73U6Q3sPhvNIrcs+YMeO0VV6DpecjoMnH5xqieZCF7flF1R2GELXOmjVrSEpKIikpCYAxY8aQlJTEM888g86k58ixNA4cOOBvHx8fz8yZM5k3bx7t27fnjTfe4KOPPqJv376kpaVRJzQK5VX+Uuk33HBDqYGYJzrTBba80tLS/BVVX3zxxVIVUk9c4LOkbUZGBjk5OcTExHD48GFWrixeCO/o0aMsWbIEvU6H3QkHD6Wyes1alFI89fxL/gVCCwsLmTBhgv+Ybq+Pwi6PAnD4SBpKKTZt2kRWVhYejwev18vgwYOpU6cOZrPZX0gt1PxXz4fX6+Xpp59myJAhKKW48soreeGFF8pUoA21GMiXAacBS5KPGkIqlApRPU43Q0Yz6fnvyFfLzJDp3r37yWeuAOg1lNvnn7nSoEGDU772xx9/XGll1Js0aVJmtsvfL+Br1qwhOTmZK6+8EoDoE6q8AsTHFcf+3wdupk3zZgD8a8jt6HU66kYVF5Vs1axJqX1mzPgRnxe8Ph8XdezIvB27mbNjN4kXdyKmYUMA2l1xBVOXLiexa/Hrbtq1lkyKE4lXXnmF999/H6fTycSJE3nllVd49dVXeffdd0u9TojZQJ70fAQsue1SA2xxFHLU6aZHlKx7I0Qg0Uw6irZnkVVQfJHL++0QmYXbKMzfR559CyZjNBoGUBoojXCvnvTsoxw9PJO9KatRKFat3klIiJFDqRNonjDWf+ySMuo//PBDueNyu928+OKLAFgsFn/C5Ha7+fnnn4Hi20nz5s3z7zN10kQ2fjoZgGcffpDU9AwKnC56xtdny9Lixe/cntIX88xMFxZjEEsfeo/N23diBr7//FsiNI30zCx0wLs+Hb2Pt9cB/33te5KaNEQflsnu2EYMPlTcS5LXPJGClOLpzJseeobRBRq5WXZ0kVHMnj6NyHHFycXvv//un447bNgwDAYDX375JatWrSoV2++7M8ktPPvCZKJqSc9HgEt3uslxeyXxECIAWdvWQWc24DlWAIC3wIMvz4Wv0IvOa0F5fKBAaT6U3ktS02YsS12FJ+4IOr0VvT6YVSuPkZgYTmrqV6WOfT5l1E8cgHnFFVfQrVs3unfvTteuXf1rycyePZuJEyf6281evIQ5m3cAYIqIQtPr0et03DninzjQExUV5b+dAmC1WLEXZhAfcxG/BJkxGw20atKQIx4P9RoU39ppHVePL+Jj/ftEh9lY53GjvBo2vQHv/F/x3ZHM0Z5JjOnUDrxeDEYj08J13P/nEtxL5nH3oMGoLRtQRh1zFyxk3bp1pKSkkJ+fz2effcaff/7JsmXLSE5OLlUHZMN/+rL/lf4nrQMiqp8kHwFurT2fzuHB1R2GEOIkdJdEcLgrHO5S/Dy7hSL1Uh+53b0cuvgNJqWu5D9rZtPsoUE0+9cgnpj8Lodyspg624nJ+DDLfruIuXP38OCDd6LUX70KZ1tG3eFw+Bf5hL/KxR8+fBhN09i3bx+TJ0+mS5cutGvXjttvv53Dhw8DMHr0aH+5eICLO3Yk01G8hs3tQ4biU+BTip9Wp7A7NRVnQWGp2zJOlxOv10ti48uZsmE1RW4Pr0z6CK/Xy6G84vErmw8eYcrC3/37pOfaKXC5KPL5iA4Px+1y0btnTwDWL1oAQJDVyj86X8on777DRx99xMBr+uDOd+DZv4frrxvA5ZdfDkBeXh533303SUlJjBo1ikGDBpUqdDbum+U0H/oKADfffHP5f7iiclVohZEKIEXGSvs9O09lu9zVHYYQ4iROVYDsjjuuU/MXNFV33PGPk5Zr/3sZ9YMHP1MLFrbwtznbMuqnKxc/btw4de211/pf/1RtT/ew2WyqQ4cOp22j03QKUPHx8aViN5lMKjIyUgGqYcPiwmn/93//pwC1rnkLtfTHmernn39WiYmJClBms1mZTCY1fvz4Uuc4c+ZMBSjrTYNV05at1ZdffqkaNmyovvzyS9W3b1/Vtm1bFRkZqaZOnVpqv09+36vCOv1DNWvWTPl8vnP8CV84FgRYkTHp+QhwuW4vZp38mIQIRKcajDp58lsAvPfek2c1GFXTGVDK4+9ZONsy6mcqF//kk3+9/qnaAkyfPh2lFK/dOoAfJr7j/15ubi7r16/nyiuvZMA1fXj22WcZ/+zrAPzrX//CZrPxzr3zWPP2z+zZsweAli1botPpSEhI4M4770QpxcGDBwHIycnBZrNh0elw5efTv39/Nm7cCBSPU0lISPDfFipx9OhRrCGheLZv5qLOV/Loo4/yxBNPcNttt3Hrrbeyf/9+Ro8ezUsvvVRqvyAj5G1exKC7hp60DkhtE2jvgAw4DWC7C4qINhmkoJgQNYzBUFyh9NixORQU7EHhA+X769+/fX0krXhQqVIeNO3863kUH0sxb948jh07dtKiaT6fz7996dKlOBwO0MOhtT8zecxP6HVBKFVcLyyo4DCrt2TS8bLOeDzFgzjnzJhHo6jiVWgPzvqZzG8exawZmbr/KOF6He2yj/Lz5EnctHI+2vESHb9N/ZjWxz9MfbfsY+7ZGlLcfwJgCuKgrSX//WIGM4L7lJwEx36chqrTHJWaRtHlIRQUFKA7foySOiA+nw+fr3QdkI3L5uMrcjDgptsr5P0UFUuSjwDi9PlYby/A4S3+JWpgNtIpTMZ7CFHTGI1hmEzRHDw09fgWHZpW/Cj5+sR/lfIQGpp4/HnF6NChA4cOHSIjI6NUqXhN03C5XKSnp/u3Hzt2jEOHDqGrF02QaSc/LDmAPV/jgZs7g6bRr8dFLJwwk19//I5L2xeXed+VuoN7b7kTWMDu6M3MP5xDkcvE5hwHPTsk0Kt9M6ZPnc1/HAVcnlA8hXZDfiH39b2M90K9pLTMI3jJtxRkFvd0NOxwKZcMG86PD92Ibdu3tOp9A4c3rOTAtmX0fvpdFr4zDm+RlwEDBvDiiy/SqFEj0tPTAXj33XcZNmxYqfOfN/1LrE0vxhJWtnCcCAAVda+nolxIYz48Pp86UuRSG+35an1uvvrTnq822PPVRnu+2pRXoLbkFaiN9nw1LyNXzcvIVUsy7cru9lR32EKICuDzeZXP563uME7qVOM/7rzzdjV/QVN16629yoxVeeutt066z4239leJUxNVr+s7q3bt2pUaq3KqfWK7JKo2H16hhgwZotq2basA9d577/lj+/uYmCKXR5kbXqSSku9QdrtdjRw5UjVq1EgZjUalaZp66qmnlNPp9Me6b98+pdPpVJ2B/6eW7TxWZe9rIAu0heU0pf5WVaaa2e12wsLCyM3NxWYL/OmlSikOOd3syi+ipNOv5N6aToM6JiN1jAb0mnb8N08Vd2VS/NCAuiaD3JMUQlQ7r7eQxUsSCQ1tS2zMAFTJXypV8tcL/9fH/5qR5jjMvWt/onVQe4IMbf46mCr5m1byb/FfPAVsy1lDvu8ozYqKx2n89NCVXDLiReq1u+qv/bXjuxzff/Fnb6FPTSHr4F+l7u+44w6ysrKYPXt2qfP4z3/+w6QPPsB85we8P7gT/dtVfJG2mmZRpr3SSzaU5/ott13Owa6CIvYVuvy/Ug0sRq6KDEV/gSYQ7777Ls888ww5OTn+bdOnT/cvQnUyEyZM4PHHH8flcgEQGhrKO++846/06HK56NmzJ7///rv/vrPFYmHs2LE8/fTTkowJUQ10OgshwS3Jy9tIQcEeSi78xb+Pfz3+eg4uH9TRa2zL24ViD38N4jhR8bYT0xBPbkPWbVnvb7Fnz16OeEPRWUIxhtUlc/FUPHmZxAx4BICIi6/lyJ+/8thjj/nXzPnmm2+YOXNmqVfyT1O+6y6+0xvIKZBCYwGpknthyi2Qb7sUerxqxtEstTO/sLpDqVLPPfecatOmjercubP/I8/06dNP2X7JkiXFU/B0OnX99derPn36+J/Pnj1bKaVU7969i6fPWa3qlVdeUffcc48ClMFgUG+//XYVnZkQ4nwdyytSjR//Rc3dnFau/U43TVgppYYMGXJW05T/7sRpyh2fn6veW7jzHM/swhJot12k5+MsKKXY4CgktchFv+hwDLra9an8mWee4ZlnngE4qx6JRx99FL1eT6tWrZg+fToAjRo14ujRo7z11lv07duXP//8k6CgIG677TYee+wxAGbNmkVOTk6ZMslCiMDl8Rb3ahj05fu7WDL191SmTp160n3Wr19ftvEJSqYpA4RZD5NT4CpXXBeqgBpfgVQ4PS2PTzEvI5d5mXbqmgxcW6f2JR7nYtu2bVgsFnr16uXf1qtXL1wuFytWrACgffv2FBYW8ssvv7Bjxw6++eYbDh8+jFKK5OTk6gpdCFFOx0eCoAvAW6Umgw63N9Auu9Uj0H460vNxGmvt+bQKsRJnMVV3KDVKYWEhRqPRv3Q3QOPGjQH8S4f/+uuvdO3alVWrVtGyZUt/u6effppBgwZVecxCiHPjO35tD7SLGxQnRF6fJB+BSHo+TuPSsGCOOd0syLQz81gOdo+3ukO6YIwZM4bVq1cTEhLCqFGjuOmmmwB47rnnmDZtWjVHJ4Q4WyW3OAKw4wOdrnh9GhF4JPk4DU3T6BgWzNVRNq6NDmNtbj7b84uqO6yAZ7Va0TStVJnk/fv3A2Cz2bBarfz3v//FYrHw8ssv89Zbb/Htt99y9dVX4/F4ypRJFkIErpJreyDedtFpGtLxEZjktstZ0jSNHlE25mbk0jLYUt3hBLRWrVqxdu1aFixY4N+2cOFCTCYTnTsXV0f0+Xx4vV5/mWQAvV7vL/sshKgZVADfdgH4ctUBXJ7y/U2xGHVEhZjRaX+dX0mNk6gQM3d1bizlAM6TJB/l4PT58NbCLry0tDTmzJlDWlqaf9sPP/xAbm4uPXr04NZbb2Xbtm0MGDCATz75hNdee41u3bqxZcsWbrrpJgoKCti/fz86nY7Ro0cD0LRpU3bv3s3jjz9OXl4ee/bsYe7cuRgMBm644YbqOlUhRDmVDDgNxItx/3b1MOl1HMjKL9d++U4vWfkuFAoNzX9L6Uhucc937zYx1A+3VnS4lSrgrlyVOun3HARqnQ+316e+O5Kp3N7atzTzqUokc3xOfrNmzZTRaPTPybcvmK8er1NHGU9oF2KxlJqTn5qaqtq2bas0TfO3sVgs6tFHHy1VJlkIEdj2HHOoxo//olbszqjuUCrdxkM5qvHjv6g/D2ZXdyjltkDqfNRMS7Pz6FdLp9qOGjWKUaNGnXV7FRTEkMgohkRG+bfVe/klwk+oiFq/fn02bNhQgVEKIaqDKhlwWs1xVIXI4OKZj1n5Nat2iFIq4H4+knycpSiTgSNON/FB5uoOJeDZLu+MbdvW6g5DCFEFSrrzdbXgg1lEUHHykV3DCpd5FRgC7LaYJB9nqX1oEHMyciX5EEKIE5T0fKzdn33ST9dnGmtwumF06jTfPK/jnm7vMxzYqNfIyq9Z68W4lAq4XntJPs5SgddHkczCEEKIUoLNxZeRl2dtq+ZIqk6AXcfPyKMUJun5CHzpTjcpeQXoNc2fyZt0Gn2iwqo1LiGECDT1wqysGNuTfKfnNK1OfuE73fXwVN863aya011eT7Wbdpq9TraPpkGDGjbTxeVTGAMsY5Lk4zifUvyW7cDl8xFjNtIryhaQRXOEECLQ1AurWRfj2satfBgD7HomyQew1VHI3kInV0WEEmLQV3c4QgghRIWRno8AlO50k+X2cG2d8OoORQghhKhwHqUCruejVq/tkuP2sDI3n64RodUdihBCCFEpXD6FSXo+AkOmy8PKXAf968ggUiGEEBcut1IBV+ej1vZ8/Jadx7V1wgNyPQIhhBCiorh9gTfVttYmH4HWBSWEEEJUBrdSGHWBdbmvdbdd8r1eFmXm0TZUpoYJIYS48AViz0etSz6WZTu4Jjos4ErNCiGEEJXBoxT6ALvkBVY/TBXQQcD9EIQQQojKFGjjG2td8pHr8QbcD0EIIYSoLGdahK861KrkY2+Bk1bBluoOQwghhKjValXyUddsINvtre4whBA11NKlSxkwYAD169dH0zRmzJhxxn0WL15Mx44dMZvNJCQkMHXq1FLfb9KkCZqmlXk8+OCDlXMSotYJxL7+WpV86NFwqUDsgBJC1AT5+fm0b9+e999//6za7927l379+tGjRw9SUlIYNWoUw4cPZ86cOf42q1ev5siRI/7HvHnzALj55psr5RyECAS1araLSafVrmxLCFGhkpOTSU5OPuv2kyZNIj4+njfeeAOA1q1bs2zZMt566y369u0LQJ06dUrt8/LLL9OsWTO6detWcYELEWBq1bVYp2k4fdLzIYSoGitWrKBXr16ltvXt25cVK1actL3L5eKzzz5j2LBhMjBeXNBqVfIBxeM+0pzu6g5DCFELpKWlERMTU2pbTEwMdrudwsLCMu1nzJhBTk4OQ4cOraIIhagetS756GgLZp09v7rDEELUEKcbZPriiy+edHvJINOdO3fy+uuvM3bsWAYMGEB0dDT9+vUDoGXLlnTu3JmoqCisVitt27blzjvvxOv10qBBg1KDT8PCwmSgqrignFfy8fLLL6NpGqNGjfJvKyoq4sEHHyQqKoqQkBBuvPFGjh49er5xVqhWwVY25BVUdxhCiBrgdINMmzRpwnvvvQdAnjOPrKIs1mxZw7X9rqVT10607dCW5q2b8+qrr+JwO8jLywPAZDKRm5fLypUrGTxyMFMXTOWme2/C4/EwZcoUVq5cidVq5cYbbwRg6NChMlBVXFA0pc5t+sfq1au55ZZbsNls9OjRgwkTJgBw//33M3PmTKZOnUpYWBj/+te/0Ol0LF++/KyOa7fbCQsLIzc3F5vNdi6hnZFSinmZdvpEh1XK8YUQF4alS5fy2muvsXbtWo4cOQJAWFgYeXl5+Hw+YmNjQYO0I2lEXxtN7C2x7HllDwXbCvyVnTSThnKr86r0FBoa6k9cTvTAAw/4k6JRo0bxyy+/sHPnThkvIkpZlGmnR1TlXE9PVJ7r9zn1fDgcDgYNGsSHH35IRESEf3tubi4ff/wxb775Jj179uTiiy9mypQp/P777/zxxx/n8lKVIsPtId/rq+4whBABbOnSpTz66KMsXrzYn3hA8d85n6/470daWhrpR9MByPg1A/dbbgq2FicewaHBACjX+SUeAHl5eSQmJqLT6TAajdSrVw/4q5fD5XLx7rvvsnv3bnQ6ndyGEQHvnJKPBx98kH79+pUZxb127Vrcbnep7a1ataJRo0anHN1dHeqYjFwUYmVRpr26QxFCBKj8/HxatmxJgwYNTtuuJBEB2P7n9r/2z6vYsWWbNm3C5/Phdrv9yVBRURFQPFBV0zTWr18vt2FEGYE4x7PcycdXX33FunXreOmll8p8Ly0tDZPJRHh4eKntMTExpKWlnfR4TqcTu91e6lEVWgRbaBNiZW5GbpW8nhCiZklOTub2228/Y/JRVYxGIwAvvPACAPHx8f7b3R9//DHJycl06NCB2NhYYmNj+eWXX6ReiAhY5Uo+Dh48yMiRI/n888+xWCpmjZSXXnqJsLAw/yMuLq5Cjns2YsxG2oRY+SU9B6dPbsMIIUpLTk7m3//+d3WHAYDbXVwi4OmnnwYgud8AVqxYwebtu5g/fz7Dhw/3t5V6IeJENb7nY+3ataSnp9OxY0cMBgMGg4ElS5bwzjvvYDAYiImJweVykZOTU2q/o0ePFg/MOomxY8eSm5vrfxw8ePCcT+ZcNLSYuCY6jFnHcsl2e6r0tYUQga88FU2rhKZDHxrFV7uKB/h1GfoUmjWMNpd19zeReiHiRIGYfparvPrVV1/Nxo0bS227++67adWqFY8//jhxcXEYjUYWLFjgnyK2fft2Dhw4QOfOnU96TLPZjNlsPsfwK4ZBp/GPuuHMz7QTYTRwsS1IPi0IIYDiAfaBwmwNxlmYT+eBw7GERjAfcG1bRHDi1eQ5/+q9LbkNU79+/eoLVojTKFfyERoaSmJiYqltwcHBREVF+bffc889jBkzhsjISGw2Gw899BCdO3fm8ssvr7ioK4GmafSODiPd6WZWRi6tg63EB1VvUiSEqH5r1qyp7hD8nIXFg1g3H85DZygCg5minGNEteuFKrIDEezfv5/58+fzww8/VG+wQpxGhVc4feutt+jfvz833ngjV111FbGxsTXql6Cu2Ui3yFC25JctfSyEqF0cDkeZAfTVzVi3KTmLPqLR0WVcdUVX/kjZzF310qlvMwEwZcoU6tat66+kKkQgOu9VbRcvXlzqucVi4f333z/rJacDSaHXx2/ZeZh0GtdIATIhajWHw8FXX33FiBEjqjuUUn74+G1ef/11lixZwuzZs6kfGYpJ86LT6fD5fEyZMoUhQ4ZgMNSqRcvFaQTiIAL533mCuZm59IsOx6ALxB+VEKIqrVmzJqASj7CwMMxmMzfeeCM2m43w8HD69u3L/v37AdDpdMyfP58DBw4wbNiwao5WiNOrdQvLnY5PgeQdQgiA7t27s2jRouoOAyhOLHJzc/nggw9YsWIFvXv3Ji4ujtWrV7N161Z/mz59+qCUokWLFtUcsRCnJz0fJ+gdZWNhVh69qqAGvhAi8JUkID169Ki2GPR6PV6vl549e7Jw4UJSU1P5+eefGTBgALNmzULTNEJCQggODq62GIUoL0k+ThBi0NPIYmJeRi5GnUZHWzA2g766wxJCVKPu3btTsv7m4sWLKycR0TRQyj9u40Rer5f333+fiRMnsnz5cuLj43n//fcD6paQEOV1zqvaVpaqWNX2bLh8PtbbC8g7vgBdQ4uRlkEWqf8hhDhrqTkHKVo7l33a+FLb133QhuTLutAkay06XRFBHRrA9RNBJ3fCRcULxFVtJfk4S/sLnWxyFNJG6n8IIcrJ6y3i2LG5HDj4P2Jj/0GjuLurOyRRiwRi8iG3Xc5SY6uZxlYz36dlSfIhhCgXvd5CbOx1xMZeV92hCBEQpI+vnMKNkq8JIYQQ50OSj3LwKoU3sO5SCSGEEDWOJB/lsLfQSROr3HIRQghRcwTiR2ZJPsqhqdXMEaebuRm5HCpyVXc4QgghxBkF4hxNGcBQDjpNo1tkKABbHIXMzcjFpNO4PCwEi17yOCGEEOJsSPJxjtqEWGkTYqXI62Nlbj5On48WwRa5LSOEEEKcgSQf58mi1/l7Q7Y6CpmXkYumacRbTTQLslRzdEIIIUTgkeSjArUOsdI6xArAroIifknPob0tiDiLqZojE0IIIQKHDFSoJAlBFvrXDSfX7WHmsRzSnO7qDkkIIYQICNLzUckSQ4NIDA1iTW4+G/IKMOt0JASZqW82yjoxQgghaiVJPqpIp7Di5a49PsXOgiK25xcBxfOvE4KKS7cLIYQQtYEkH1XMoNNKjQ0BWJ6dh07TZGyIEEKIWkHGfASArhGhbHUUVncYQgghRJWQ5CNANLaa+fVYDrluT3WHIoQQQlQque0SIFoGW0gIMrM2Nx+H1wcUl8QtqckfatBzyfFxI0IIIURNJslHANFrGpeGh5z0e4eLXPycnkO/OmHoZJaMEEKIGkySjxqivsVEmFHPz8dyaBcSRHyQzI4RQghRM8mYjxokWK/nH3UjcCofy7LzqjscIYQQ4pxI8lEDtQq2kuX24vT5qjsUIYQQotzktksNdU20jaXZDvRAl4gQzDrJI4UQQtQMknzUUCadjl5RNgq9Pn7PduBWiiijgQ62IPQyIFUIIUQAk+SjhrPqdfSIsgGQ6fKwOOuvsSDBeh0X24Ix6iQZEUIIETgk+biARJkMXH08EQHI83j5PceBVyl/vZBmQWaayDoyQgghqpEkHxewUIOebpGhpbatynGwq8BJ8yAzcRaT1AwRQghR5ST5qGUuDQ/BqxT7Cp0szsrD4fVxaVgwsWZjdYcmhBCilpDkoxbSaxrNgiw0C7KglGKTo5BNxxe2M2kaHWxB2Az6ao5SCCHE+fAqxbb8IlxKnblxFZPko5bTNI22oUG0Pf7c6fPxp72AHI8Xk06jS3gIJpnGK4QQAW93QRH7C13+53aPl0vDgsnVB96HSUk+RClmnc6/vkyh18eybAcepWhgMdEm2IImY0SEECKgeJViTkYuCUEWep4w6aBEfYupGqI6PUk+xClZ9Tr/f+TDRS4WZuVR4PXRMzKUYLktI4QQ1WpbfiFrcguwe7wMbRBNkL7m9FJL8iHOSn2LifoWEx6f4o9cBzluLz2iQgkOwO48IYSoDeLMJlyhirX2AjY7CrkkLLi6QzprknyIcjHoNK6ICMWnFAsy7Rh1GldGhEpVVSGEqGLBBj0xJiN6oJMtqLrDKRdJPsQ50WkavaPDyPd4WZKVhwJ8SnF1lE1qhwghRBWJMRsJNejZV+jCZtCzyVFIR1sQoQF+a1ySD3Fegg16/7iQPI+XhVl59DrJgCchhBCV44aYCLY6Cjla4Cbb7SHd5Q745KPmjE4RAS/UoMenFB5f4M0pF0KIC1nrECuXh4cQatDXiCU0JPkQFapbZCjLcvLO3FAIIUSFOuYq7vmoCTe+5baLqFBmnY4ir/R8CCFEZfP4FC6l2F/o5FCRC7NOx40xETWiHpMkH6LC2Qx67B6vlGgXQohK4lOKb49m0dhipr7FSO/osOoOqVwk+RAVrlWIhV35RXSsQXPOhRCiJsj3eHlw636Mmo5H4mNoFWyt7pDOiSQfosJFGg0sLcqjvS1I6n8IIUQF2ewoJLXIxaQ2TTjkdNGsBgwsPRUZcCoqRd/oMGYdy2VvgbO6QxFCiAuCTyn0msbyHAf1TMYaMbbjVCT5EJXCqtfRv244+4ucZLg81R2OEELUeNEmA3/mFbAzv4g9hU72Fzpx+XzVHdY5keRDVKpLwoJZb8+v7jCEEKLGq2c2cWf9KPpEhxGs17OzwMmCTHt1h3VOZMyHqBRKKRZk5WHUtJMu8SyEEKL86piM1DEVfx2s17HJUcjCTDsunyLJFkSM2Vi9AZ6lcvV8TJw4kXbt2mGz2bDZbHTu3JlZs2b5v797925uuOEG6tSpg81m45ZbbuHo0aMVHrQIbPsLnfyakculYcF0i5RF54QQojLEmI1cHWWjZ5SNvtE2Uotc/JKeg93jre7QzqhcyUfDhg15+eWXWbt2LWvWrKFnz5784x//YPPmzeTn59OnTx80TWPhwoUsX74cl8vFgAED8NXQe1Li3GS7vcRbzVLnQwghqoimaXQMC8ao08h2B/44O00pdV7lKCMjI3nttdeIi4sjOTmZ7OxsbLbibvbc3FwiIiKYO3cuvXr1Oqvj2e12wsLCyM3N9R9H1Dwb8woo9Pq4NDykukMRQohaY1WOgxCDnjYhVV//ozzX73MecOr1evnqq6/Iz8+nc+fOOJ1ONE3DbP5r3rHFYkGn07Fs2bJTHsfpdGK320s9RM3XNjSIaJORJVmyzosQQlSVRlYzmTVghmG5k4+NGzcSEhKC2WzmvvvuY/r06bRp04bLL7+c4OBgHn/8cQoKCsjPz+ff//43Xq+XI0eOnPJ4L730EmFhYf5HXFzceZ2QCBxNg8w0DzKzVBIQIYSoEl8fySIlr4A/chzVHcpplTv5aNmyJSkpKaxcuZL777+fIUOGsGXLFurUqcO3337Lzz//TEhICGFhYeTk5NCxY0d0ulO/zNixY8nNzfU/Dh48eF4nJAJLfYuJIhnzI4QQVaJPtI1ok4F0l4cFmXZW5DjIDcAxIOWeamsymUhISADg4osvZvXq1bz99tt88MEH9OnTh927d5ORkYHBYCA8PJzY2FiaNm16yuOZzeZSt2rEhSdYr6u0heZ2FRSxt8Dpn1GjAer4vxz/2qTTaB1sJcokM8uFEBe21iFWWp8w3iPf42VrfhGpzjyaWs20DQ2qxuj+ct5/jX0+H05n6RLa0dHRACxcuJD09HSuu+66830ZUYN1CQ9hRnoO19YJw3yaXrDyWpnjINSgP+NqjkVeH1vzi/gzr4CS0dVmnUaSLYhgvczIEUJcuIINejqFBZPgNjMjPYfEEGtAlGUv15Vg7NixLF26lH379rFx40bGjh3L4sWLGTRoEABTpkzhjz/+YPfu3Xz22WfcfPPNjB49mpYtW1ZK8KJm0DSNAXXC+eFoNr7zm1zll+Hy4PD6zmpEt0WvI8kWRM8oG1cff3SyBZNiL2B+pp35mXaWZOWx3l7AFkch2/OL2JFfRI7bw3lOBqsRli5dyoABA6hfvz6apjFjxowz7rN48WI6duyI2WwmISGBqVOnlmmTmprK4MGDiYqKwmq10rZtW9asWVPxJyCEOKMinyLOYgqIxAPKmXykp6dz11130bJlS66++mpWr17NnDlz6N27NwDbt2/n+uuvp3Xr1jz//PM89dRTvP7665USuKhZDDqN5Ogw5mfaWZBpx3mO40C8SrEo0862/EJ6RoaeczwWvY6uEaH0irLRK8pGl/AQGltNRBoNhOh1BOl17ClwsjgrjwXHY16QaWeLo/CcX7MynU8CcfXVV7Ns2TJuvPHGMm1OlkD8+OOP9OvXjx49epCSksKoUaMYPnw4c+bM8e+XnZ1N165dMRqNzJo1iy1btvDGG28QERFRkacthDhLXx/JonMAlT447zofFU3qfFz4nD4fczLstA+10vgsl4Tenl/E/kInOk3j8rBgQqqpgNmhIhdbHIVoFK9bE24MjHEks2bNYvny5Vx88cUMHDiQ6dOnc/3115dqs3TpUl577TXWrl3LkSNHMJlM/Otf/6JDhw68+uqrbNq0CYAnnniCl156iezsbFq3bo3b7SYvL4/69etz0003kZeXx9y5c4mIiGDz5s3Uq1cPh8OB3W5Hr9eTkJBAx44d2bp1Ky1atGDWrFkUFBSQkJDAlClT6NSpUzW8Q0LUTjOP5ZDh8pDn8XJJWDCXVWICUp7rd2D85RS1ilmn47q64WxxFDL/+KJIBg3ahQYRecLFPN/rZWVOPh6laBlsoc8ZxnZUhYYWEw0tJrxKsTY3H4e3uAdHAc2CzDQ5y2SqvP6eOPw9uUhOTiY5ObnUPosXL2bMmDFs3ryZuLg4rrvuOiIiIjAYit9jl8vFm2++CYDRaESn0+Hz+fxT48eOHcuxY8e48cYbWbp0Kfv37+eNN97wH79ly5b897//5dprryU7OxudTofH42HTpk3+RGbdunUEBQURHx/P1VdfLT0fQlShfK+XTXmFNA0yM6RBdHWHU4okH6LatAmx+sdsuH2KDXkFpHgK/N+36HRcGRGKURcY9yhPpNe0UtVblVLsOr7CpKI4mWofGkREBfWM5Ofn0759e4YNG8bAgQPP2P7o0aMMGjSI++67j88//5wFCxYwatQo/vOf/7B///4yU9rHjRsHwOOPP47FYgHgu+++w2az8f333/uXSLBYLBQVFQEwd+5cwsLCaNmyJevWrcPlcqHT6ejYsSPr1q1DKcVVV13FqFGjSEtLY+TIkSQlJdGsWbMKeU+EEKf38aEM6pgM3BwbWd2hlCG3XYSoBG6f4s+8ArLcHuIsplJT386XpmlMnz7dv7TB33tDNE0jNjaWjIwMPB6Pf3vPnj1Zt24d+fn5eDyl5/23aNGC3bt34/V6sVgsdOjQgT/++KNUG71ej9dbdsEqk8mEy+XyP69fvz6HDx+mbt26WCwWf6JjtVpp1qwZGzZsqLD3Qghxam6fYmt+IekuD0E6HV0iKnfMR5WUVxdCnJpRp9EpLJheUTYOFrnOvMM5KOkNef/998t8z+Px0Ldv31LbmjRpQm5ubpnbMwA7duzw19vxeDysXLnS/z1N0zCZTP7bNX93YuIBcPjwYaB4gLrX62XatGmMGzcOp9PJ/v37y3eSQohzZtRptAsNoleUjXSXu7rDKUWSDyEq0bJsR6WNME9OTmbcuHHccMMNZb5nNBrp2rVrqW0l6yZ9/fXXZdrHxMRw0003AcWF/2655RagOPHQNA2fz0dsbKy/wODpREVF+b9OS0vD5/Px5JNP0rZtW1nhWohqkuH2cNQZOAmIJB9CVDClFFsdhczLyCXUoCe0mmbmlPAVunH8cYQt64sHgTpWl11rqXnz5qSnpwPFPRkbN24Eis/F5/Ph8Xiw2Wz+Xo1TCQoKKtXj4vV6ueeee2jSpAkbN27EaDRW1GkJIcpheMM67Cl0Mj/TTqG3+j8ESPIhRAU4MeGYl2knWK+jd3QYSbYzlzJeunQpXbp0wWKx+HsazlSnY9OmTbRo0QKdTucvGvT111+TkpICFI+veOGFFwC48Y5bCO1cn617tgNQt1vZAZ/Lli1j9uzZALjdbrZs2VKmzcaNGykoKCiz/URKqTI9K16vF6fTic/nK9UrIoSoWpeHBdMuxMpHh45VdyiSfAhxvjw+xfT0HH/C0Sc6jEZnmHJ7YlGwbt26sW3btjNWHiwpCgbw9NNPs3PnTpRS6I+XiP/qq69ISkoCYM+ePRQWVn1BtMjI0qPqdTodHTp04I033vDHKYSoHr/nOPjkcCaNrKbqDkWSDyHOlVcpVuY4mJWRyzXnkHBYLBYeeOABAHJycvxTWAH/gM+ShMNoNNKjRw//NNhScfxtBorRasQUXjF/XOIj6pyxzYl3UlJTU0v1bvh8PjZv3swLL7zALbfccsaeEyFE5ekaEcrAmAgCYY6rTLUVopyUUizIykMpxaVhwYSdoZZHSYGwBQsWlOmNOLFuxt81bNiQQ4cOVVjc5yI+sh6t6zTj1+3LSm3XNDCZ9CgFFosBh8OFz1f6T4ler2fixImMGDECgNGjR7Ny5Up+//33KotfCFHavIxcDJpGj6iKv77KVFshKtG2/CKaB5npHR12xsQD4PXXX+fXX3896W2Qv68IfaLKTjz+fpPnZMW/9mYdKZN4WKxWQMPp9OLxKPLyXCgFV111FUajEZPJxPPPP4+maRw7doxdu3bxxRdfMHnyZB588MHKOyEhxCl5lWLG0Ww62IIqJfEoL0k+hCinZkFmVufmY/eULbh1MmFhYURFRRESUnbKbXV2PJa8cskMlN27d5dpExMTg8lU+haOz+v1l0n3+XzUrVuXiIgIVqxYQUhICA0aNODpp59m+vTpfPnllyQmJvLCCy8wYcIE/wrYQoiqtb/QRdMgM3VMgTHjTG67CHEOfErxW7YDq650mfVTmTVrFq+//joLFy6sgujOzaBBgygoKGD69On+bfHx8XzzzTdcduml6DQNo8lIQWHxbaLQ0FCsVivp6el8//332O12ioqKGDduHKmpqdV1GkLUekopsj1e0pxujjrduJUi2mSgoy24Ul9XFpYTopLpNI1ukaHsLihiQ14B7UJPP6W2pKpooCUfwXodTq8PD/DVN1/jdReXXdco7hm5NimRDb/8QEhwMHn5DprWrcPy5ctRStGwYUN27drF0qVL2bhxI7GxsezYsYPGjRtX5ykJUevkebz8nuPAeMKMuXCjnnpmIy2DLejPMJOuOkjyIcR5aBZkYW5GLu1Cz9z2ZGXNq5vHp/xjP7xuD7qISHyOPAwo3G4PmzdvJrjAjs/jRim4vGMSS5cuRdM0zGYzHo+H8ePHk5iYyI4dO5g8eTKTJ0+u1nMSorZQSrGn0Mnq3HxujY0843T9QCLJhxC1mEspSt13zc1BUz7cCsxGA5uO5bBkx16UUmiaRstLLufmm29m1apV7Ny5k0ceeYQ5c+awePFi4uPjZVyHEFXot2wHQXpdjUs8QJIPIc5LttuDRXd247YdDkclR1N+fx/w5fP50DSNJmGwL9eDMyuLUIuJceNfomnzFowdO5bnn3/en2iMGDGC119/vVpiF6K2y/N6aWw11bjEAyT5EOKcbXEUsr/QyTXRYadt53A42LVrFwsWLKiiyM5du3btuP++EYx++CE6NLCxO9NJnfAwRowYgTUklP79+1d3iELUek6fD5dPsbfAyWVhlbNwZWWT5EOIcsj3elmdm4/Tp2gdbCG5TvgZ9/nxxx8ZPHhw5Qd3lvQ68Pr+GlRawmwycUnbFtx3c1+2TDXxyyETOrNGkc6ANeQsBrUIIarErGO5hBn0NAsy88uxHIY2iK7ukMpNkg8hztIfOQ7yvT6ujAjBdJa3WgBWrFhRiVGVT4gJoiL0HDzmLS6xfDz7iA4CDTfbf5sO782ldbSO/23MwxYeKbNXhAggXx/JIt5qOqsp/oFMiowJcQYZLg8/pefQLMjM1VG2ciUeAO+99x6LFi2qpOjKp8gDeQUGfD6Ol0Y3YTQYaNA4gSynxu+HfDxyKJmvMlpRUOQiKytLqpIKEQB+y8pjfqadtqHWGp94gCQfQpzWVkchmxwFXFc3/LwqA3bv3r1aExAtIoogA3h8kJXn9Fc1TUq6GI/Xy6Yde7njjkHExMTy5sdfs3RVCjabjXfffVdmrwgRAAp9PppZzbQJsVZ3KBVCkg8hTuFQkQu7x0v3yIqptFudCYg+zILLV/x1ZIiFLVu28Pnnn/Pnn3/Su3dvEhISWL9+PVlZWbRq1YrJkyeTk5PjXxROCFG9+kSHken2MD/Tji+wCpOfExnzIcRJKKVYby9gQN3wCj1uSQLSo0eP07YzGo243e5yHdsWXQd7xjEwGCAoBOw5JQcj4YXWPJkOjzydigdFYmKif7qsx+ORkuhCBKh0p5sVuQ6C9Xo0ipd2qPmphyQfQpzUipx8ukZUzn3V7t27+xeUa9u2LZs2bSrTxu12M2TIEKZNm+bfdv91T9AqqjHjv/83R+35pdrbHnsOz4G9GFYuI+rjbzk2+Dp8x5MPY6tECm3XsCd7F72aGjio1eO3DXv9+44ePVoGlQpRjYq8PtJdbvK9Pgq9PuxeL97jGUaEQc91dcJrZC2P05HkQ4i/UUph93iJNFb+r8fGjRtP+T2Hw8GoUaMASEpK4uixXII9fzD8ysuoE92PmX+uwVunkIf+7w1cSnEo9QBjZ3xN24nv0fG5SexO+YPpE8fTuX8PGqcdxlTn/xhy7yb6j3mP8ePHc8stt7Bq1SopiS5ENdrsKCS1yEW81UyYQU99s5FQgx7dBZZs/J0kH0L8zR+5+VwaXrmrP56NNWvWlLo988OKiQDccFFf/nPJ5SzeupjM7Eyuv6rp8RbN6Fj/V0aPHs2EHz+lYcOGfPzxR9xQrzsF69Opd++lAEyPv7pMpVIZVCpE9XB4vBg0jQNFLmLNRupbTNUdUpXQlAqskSvlWZJXiIqW4/awOjef3meoWlqdjk5YizutwP9cH2khpHM9gi+rh86kL9M+d+4+CtamU2/spVUZphDiLHmVYvrRbDragmkaZK7ucM5Zea7f0vMhBMVTag8WuQjW6+gVFdhJb9i1TXHuywVNQ7m8FG3LInfmXnJn7iXs2nhCr2pYqr2m04qLegghAtImRyFXRYRS13zu0/lrGkk+RK2WYi/giNNFq2ArfQK4t+NElhYRWFpE/LWhX1MKt2aSOW0Lub/uxbk3F3Qaml4DnYbnaIHkHkIEqM2OQo463bQPDaruUKqUJB+iVkotcrHeXkCnsGA62Gr+L721dRS2a5rgOpBX3Mvh8eFzKfAqNLOeoKY1I7ESorbYX+hks6OwRn3wqUiSfIha55jLzfb8IvpXcA2P6mbrHlfdIQghTsHjU+wtdHKwyIXLp2hkNXHtWSxMeaGS5EPUKhkuDytz8i+4xEMIEZg8PsWS7Dx8StEi2EL3yNALfhrt2ZDkQ9QaTp+P33McXCeJhxCiCiil+OVYDn2jw7DqZTWTE8m7IWqNfYUuLr4AxncIIQJTkdeH94TR3WvsBXSNCJHE4yTkHRG1hsPjJdRQtg6GEEKcrQKvjzW5+SzNysPu8fq3z83IZY09n48PHfNvCzfoKfD6qiPMgCfJh6g1NA3cPplzKoQ4N1sdhSzLzqN5kJkwo54UewHZbg+/pOfQMtjCFRGh1DUV1+oo8vrYkFfgfy5Kk+RD1BrtQoLYkFdw5oZCCPE336Vlkevx0ic6jDCjgU15hRT5fGzPLyK5ThiNrcWVSZNsQSzMtLMqN5/r6kbILZdTkAGnotYw6DS8Z24mhBD8mJ5NodfHNdFheBXYDHrSnG7/9wfVjzrpfo2tZn8iIk5Nkg9Rq5g1jTwZ+yGEOIN+0eH8mpHLkuw8iryKW+tFVndIFxRJPkSt0jUihOlHs7mubgRGncy1F0Kc3G/ZefSNtmHWyW2TyiDvqqhVdJpG/7rhzMnIZW+Bs7rDEUIEqFYhFhZl5pWaOisqjvR8iFrHrNPRv244m/IKmH0sl4YWIy2CLZjkE44Q4rh6ZhO2SD0LMu0AtA6xEmcxVXNUFw5JPkStlRgaRGIopDndrMrNx3l8Gq5Vp+Py8GApgSxELRes19MnOgylFNvyi5iXkUuU0YBLKeweL+1Dg4gxy1TacyHJh6j1Ys1GYk/4A2L3eJmbYae+xUi7WrbMtRCiLE3TaB1ipXWIlSVZeSzKstMlPASDfEA5Z9LPLMTf2Ax6rqkTRohez8xjObh8UqFQiNoqz+Nle34Rx1xuDhe5cPmKp9/2iQ4jyiSf38+VvHNCnELTIDMNLUZ+PZZL14gQ6kilQiFqlXyPlwWZdjqFBXOoyI1PKXpHh1V3WBcEST6EOA2TTsf1MRH8nu1gvb2ApkFmEoIs1R2WEKISrMvNJ9vjRQcowKMUXSNCcPkUSbIoZYWS5EOIs9AlIgSAXQVFzM3IRQOaWM00D5ZERIgLxf4iF9HHB5RqgF7T2OIoItXp4vq6EQRJqfQKI8mHEOWQEGTx93zsLXAy//g0vJJhZxpg0DQSQ61EGuXXS4ia5Pq64biVKjXtfn+hkyKfTxKPClaud3PixIm0a9cOm82GzWajc+fOzJo1y//9tLQ07rzzTmJjYwkODqZjx458//33FR60EIEgPshMrygbvaJsXH380TPKRufwEPYWOFl0PDERQgSuPI+X5dl5LM3KY3mOg5U5+SzItLMg0878TDt5Hi99ZZxHhSvXR7OGDRvy8ssv07x5c5RSTJs2jX/84x+sX7+eiy66iLvuuoucnBx++uknoqOj+eKLL7jllltYs2YNSUlJlXUOQgQUo07j4rBg5v5/e3ceHVV99w/8fe/sk8ySTBLW4EIg7LsPBlSssghWraU9PdZqF6qiHtvTWq380Xr0HMVKradHW0p/4qlU0WJ/RX18kEUERUWWkCCRRUR4WAwGssy+38/zB8lICEkmy2zJ+3XOnEPu3Pny/cyde+cz3/tdzrrxv8EwF5kiymL/+boRswptiDXP3TEqzwKLqkDhMNqUUkR6NndsYWEhli1bhkWLFiE/Px/Lly/HHXfckXje5XLhD3/4A37+858nVZ7H44HD4YDb7Ybdbu9J1YgyrsYbQG04CgFQajbCadDBH9dgVlUMNhk4kRlRhkU0DYcDYZyNxHAqFMEkuxVj8i2ZrlZO6sr3d7dvYsXjcbz22mvw+/2oqKgAAMyYMQP/+te/0NDQAE3T8NprryEUCuHaa69tt5xwOAyPx9PqQdRXjLNZMafIgTkuO+x6HZqicRgUBf64hnVn3Hi/wQtvLJ7pahL1W0ZVxdh8C5piMfxwsIuJR5p0uUfcvn37UFFRgVAohPz8fKxduxZjxowBAKxZswY/+MEP4HK5oNfrYbVasXbtWpSVlbVb3tKlS/HYY491PwKiHKAoCoaYjRhy3rbyPDMimoY9ngDqozFMtFkxlGtHEGVEqcmIw/4QR7ClSZdvu0QiERw/fhxutxv//ve/8cILL+D999/HmDFj8MADD2Dnzp148sknUVRUhDfeeAPPPvsstm3bhvHjx1+0vHA4jHD4m9VFPR4PSktLeduF+p1qTwC14QimOfJaTWgW0wSnwhGcDEXgNOgxlr/MiFJi3ZkmLCh2ZroaOasrt1163Odj9uzZGD58OB5++GGUlZWhpqYGY8eObfV8WVkZ/va3v/V65Yn6GhFBtTeIpmgssU1VFAw2GVBqNuJwIISPm3y4sdjJVhKiXuCNxbGt0QuzqiJPp2K6Mz/TVcpZXfn+7vFEBJqmIRwOIxAIAADUC5Yl1+l00Lg2BlFSFEVpM5PikUAIRwJhnAhFIACuLrAx8SDqARHB2WgMRQY9dIoCs6riOhd/7KZTl5KPJUuWYP78+Rg2bBi8Xi9Wr16NrVu3YsOGDRg1ahTKyspwzz334I9//CNcLhfeeOMNbNq0CW+//Xaq6k/Up20868ZlFhPmcp4Bol7z/06ewSCTEQLAqlO5eGQGdCn5qKurw5133ona2lo4HA5MmDABGzZswJw5cwAA69atwyOPPIKbbroJPp8PZWVleOmll7BgwYKUVJ6or5tqz8Mnbh/KrKak5x0IxjVUewMQAaY6rDCpnJmRaHO9BwqASXYrFg0txpeBMOoiUURFoFNV/HddE8bkmzGcazelRY/7fPQ29vkgaq0xGsP7DV7cWOyEQW0/AfkqFMFebwA2vQ6TbFYoACo9AYQ1DYqiYKTVhGGc8Iz6qQ1n3RhsMiCsnZtMTIDEAnICQGueZGzhwMLMVjSHpbXDaW9j8kHUViiu4eMmHzR8c8E0qwo0AcLNp3CRQY9J7ay8KSI4HAjjSCCE+ezNT/3UiVAElW4/bi5xcoK/FEhrh1MiSj2zrm2HuGBcg05Bq0Ww2qMoCkZYTTgSCOHDRi8AoNhowOUWU4etKUR9SanZiEKDDm/UNWGey448vS7TVeq3mHwQ5ShLF1fZVBQF84ud8MbiMKoK6iIxfNTkRVzOtaRENQ3XFNqQp+MFmfquPJ0ONxU7sdPtQ1g712oYF8F/OfLg4ErUacN3mqifsTX/2is1G1F63pDduAg+avQhrGmw6FRMs+fBzGXEqY/4KhRBtTeQaCm88JN9Nhpj8pFGfKeJCACgUxRcU2gDcO6Wzi63P9GfZFy+BQNNho5eTpTVCgx6qFCgAhhvs0AT4HAghLAmEADDzOyMnU5MPoioDYtOxdXNiUjLrKv7vAHM4XwjlKMsOhU3FDsQ0TQc8IegAzDNnoeICN6t9+BcCsL+T+nCNlUi6lDLrKux7BoYR9QtRlXFRJsV42xWmHUqPmny4dYSZ1Idt6n38N0mok4F4xr0HJpIfcwutx+DTIakJ/Cj3sPbLkTUKYtOhV2vw3vNs0S2tIHUR2MobF5pl31CKFecDkex2+3HBJuFE+9lCJMPIkpKe6t9aiL41BtElcePG4oc/BVJWccTi2OPx4+YnOvVUWTU48ZiflYzickHEfWIqiiYZLdieMyETfUe6BUFCgCDqqDUbMQQkxF6TmRGaeaJxbGjyQcAsOt1mOm0cUK9LMLkg4h6hU2va7X6bljTcCIUwcdNPsREEBNBeZ4Zl7CZm1LsoD+ILwNhzGdLXNZi8kFEKWFSVZRZzShrXiU03jykkckHpYonFsd79R5MtFmxgGsYZTUmH0SUFkcCYYzK43LllDqbzrrx3QEFbO3IARxqS0Rp4YvFuZIopZTDoGfikSOYfBBRWky2W3E0EE50AiTqbSqA+kgs09WgJDD5IKK0UJrXjrnEYsL6M25UewKZrhL1Md8qtGFboxf+WDzTVaFOMPkgorQaaDLghmIHiox6bDrrznR1qA9RFAU3lzixsd6T6apQJ9jhlIjS4n/ONMGiqomluzQgMRKGqLeoigKHXoc9bj8m2a3sZ5SlmHwQUVqYVRXXueyZrgb1A9e57DgTiWJLgxcxEUyyWTGA0/9nFSYfRJQWcRGICEcjUFoUGw243mWAiKDKE0CVJ4DrXXbOcpolmHwQUVpc6czHm3VNuN5lh02vy3R1qJ9QFAVTHHkIaxq2NXqhASg26jHRZs101fo1djglorSw63W4pcSJzfUejkagtDM13/ab7bJDBXAkEMp0lfo1Jh9ElDYtoxG2NHhxOhzNdHWonyo06NEYZQKcSbztQkRppSoKvl3ixAcNXjREYxiTb8l0laiPCcY1eGNxxEQQBxCKa9ApCoyqgt1uP4aYjbjCkZfpavZrTD6IKCOuKbThsD+E9WfcuMRixGgmIXQeEUFjLI6GaAyhuIamWBxRTb55/iKvaelKalQV2PU66BUFOkWBWVWgAfDG4ri5xMnht1mAyQcRZcyIPDNG5JlxLBjG23VNmGS3YqjZmOlqUZrFNEGVNwBPLI7z0wKnQQeXQQ+70YAReWaYVPYU6CuYfBBRxl1qMeFSiwkfN/oQjGsYwdVvc1ogruHLQAgREYzJs8Csu3jSUOn2oyEag15RMNluhdPAr6T+gkeaiLLGjIJ8bDzrxkCTgcNxc8iZSBR7vcFEq4VFVTHcaoJBVbDb40dIOzfHy1UFNhhVBXs9AZyORDHVnoep7HvRLzH5IKKsMsdlx3+fcePmEmemq0KdiGmCDfVuDDIacH2h7aITyF1VYANwbpK5Dxt90EQw3mbFFCYd/RqTDyLKKkpzB0HKfhvq3ZjtsifVF0OnKJhVaEtDrSgXsPcOEWWVunAUxUauw5HtzkSiGGA0sBModQtbPogoY0QEYU3gjcfhicXxv8EIQpqG+UWOTFeNOlHjDeJKZ36mq0E5iskHEaWVJoKPm86NatEpCkzNczLY9DpcXWDjwl85oMYbgEOvg6WdUSxEnWHyQURps8vtR2M0hv9y5HFYZY7a4/ZDryrsMEo9wrOfiNKiZS2XubylkrN2NvlgN+gwKo+z0VLPsM2MiNKiLsKF5HLdF4EwRlo5ARz1HJMPIkqLCTYrhpoNeKuuCWeYiOSkwWYDlh09nelqUB/A2y5ElDaDTEbcVGzAbk8ANd5gYnEwo6okJqOi7DWrwIYCg56LAVKPMfkgorRSFKXVcub7fUH0pfEtUU1wJBjC6XAUgbiG1bUNePiygSg06PF2XRMGmgy43mXPyenjFUXBRJsVE23AkUAIm+s9uN5lz3S1KAcx+SCijDoWDGNBsTPT1eg2kXMrsjZE4wAAvQKUWc24usAMnaJgXpEDjdE46qMxzCzIRzCu4YAvCF9ca7MsfJFRj3Krud2F2LLJcKsZNp0OG8+6oSoKptqtKOAIJkoSPylElFGTbFbsaPJheo5NWBXWNHzU6ENUBFPsVkyxX3xWVp2ioMioR5Gx88vtmUgUuz1+hLVv0hKbTsVlVhOKDPqLrp2SSSUmA+aaHNBE8FGjD0VGPW/FUFKYfBBRRg02G9EQjWF7kw8VOZCA1EdiqPT4YVAUzHDm92orRbHR0GZqeW8sjqPBMPZ5g9Cat1U48pCXRbdtVEXB1YU2vFvvwUCTgS0g1Cl+Qogo48bZrDgRimDjWXfWzgNSH4lhl9sPl1GPOS572lohbHodJtisib9jmuATtw+BuIYCgx6TbVbos2RW2OsLbXj960YsHFAAXZa10lB2YfJBRFmh1GyEAmDjWXdav9yT4Y3Fsb3Jh2+XODNdFejPGxnUGI3hg0Yv4iLQKQqGN9+eEQAxETj0urS+j4qi4MYiB96qa8KtAwrS9v9S7mHyQURZY6jZCLtehzfrmjDFbsUwiynTVYIvFsfmeg9uzoLE40IFBj2uax5tEhfBkUAYn/mCAAC9osAdi7fq1GrX63C51YTCFN4W+ajJxxEw1CkmH0SUVex6Hb4zoAD7fUFsPOuGSVUx3ZGX9hEgDdEYdrvP9e24ucQJNYtaYi5GpygYmdfx7KPuaAxfBiPY6wlAAyAALKqCSXYr8nQ970PyYaMXI6xm2LOoPwplJyYfRJSVxuRbMCbfglBcwweNXgyzGFO+pkhcBO+cccOsU+HQ67Lu9k9POQx6TL6g1cMfj6PaE4A/rqHU3P2Jw0QEVZ4ArrqEk8VR55h8EFFWM+tUzC1yYN2ZppQmH1WeAI4Gw8jTqZjdj24b5Ol0mNnch+RIIIQ36xox3GLCiDwzTGpyrU1fh6PY3uTDT4YUpbKq1Id0KflYvnw5li9fjmPHjgEAxo4di9///veYP38+jh07hssuu+yir1uzZg2+//3v97iyRNQ/NUVjMHTSArHhrDuxjwZAByAqAn9cw7eLnTC0MyJERPDOWTfG5Vsw2d6/O0kOt5pxucWEKk8Au9x+RJvnGzm/34hy3t8t/3Y23yojSlaXko+hQ4fiqaeewogRIyAieOmll3DLLbegqqoKo0aNQm1tbav9//73v2PZsmWYP39+r1aaiPqXHW4/ri1svzlfE0FDNIarC2wYYjK0ulUS0TS8VdeIG4ocF50bY1ujDzOd+XBwbgoA50asTDlv+nuiVFBE5MIZfruksLAQy5Ytw6JFi9o8N3nyZEyZMgUrV65MujyPxwOHwwG32w27vf80fRJR+2Ka4INGL2IiMCgKLreaMMxsbJVkiAgO+kOoDUcTv8wrnPmw6lRoItjW6ENY0zDIZMC4fEvitZvOujEnS+cWIcolXfn+7naqH4/H8frrr8Pv96OioqLN85WVlaiursZf/vKX7v4XREQAzs1tcf6Q0qPBMLY0eCE41+oxKt+S6CzZ0mEyqgn+/9cNuKnYiTy9DrOaW06+CkWwqd6DQoMe0xx5KLUYscft5699ojTqcvKxb98+VFRUIBQKIT8/H2vXrsWYMWPa7Ldy5UqMHj0aM2bM6LC8cDiMcDic+Nvj8XS1SkTUj+gUBWVWM8qs3wwr/ax5WK5Dr8MVjjyoigJfPA6zqra51TLYbMRgsxHbGrzwx+IYlWfBl4EwNpx1o8RowCSbpU+NcCHKRl0eOF9eXo7q6mrs2LED9957L3784x9j//79rfYJBoNYvXr1RW/FXGjp0qVwOByJR2lpaVerRET93Nh8C+YWOTAyz4ytDV5srvfgsD+EWzqYGGyy3YqPmnwAgMutJswrcqDYqMfKU2fx52NfI6xp7b6WiHqmx30+Zs+ejeHDh2PFihWJbf/85z+xaNEinDp1CsXFxR2+/mItH6WlpezzQUQpdyIUwSF/CCrOjdowqQqGmIwYbDYkPcyUiM5JS5+PFpqmtUoegHO3XG6++eZOEw8AMJlMMJkyP4UyEfU/pWYjSs3GTFeDqN/pUvKxZMkSzJ8/H8OGDYPX68Xq1auxdetWbNiwIbHPF198gQ8++ADr1q3r9coSERFR7utS8lFXV4c777wTtbW1cDgcmDBhAjZs2IA5c+Yk9nnxxRcxdOhQzJ07t9crS0RERLmvx30+ehvn+SAiIso9Xfn+Zo8qIiIiSismH0RERJRWTD6IiIgorZh8EBERUVox+SAiIqK0YvJBREREacXkg4iIiNKKyQcRERGlFZMPIiIiSismH0RERJRWTD6IiIgorbq0sFw6tCw14/F4MlwTIiIiSlbL93YyS8ZlXfLh9XoBAKWlpRmuCREREXWV1+uFw+HocJ+sW9VW0zR89dVXsNlsUBSl18v3eDwoLS3FiRMn+uSquX09PqDvx8j4chvjy22Mr/tEBF6vF4MHD4aqdtyrI+taPlRVxdChQ1P+/9jt9j75wWrR1+MD+n6MjC+3Mb7cxvi6p7MWjxbscEpERERpxeSDiIiI0qrfJR8mkwmPPvooTCZTpquSEn09PqDvx8j4chvjy22MLz2yrsMpERER9W39ruWDiIiIMovJBxEREaUVkw8iIiJKKyYfRERElFZ9MvnYs2cP5syZA6fTCZfLhbvvvhs+n6/VPr/4xS8wdepUmEwmTJo0Kalyr732WiiK0uqxePHiFETQsVTFFwqFcP/998PlciE/Px8LFy7E119/nYIIOpZMfMePH8eNN94Iq9WKkpISPPTQQ4jFYh2We+mll7Y5fk899VQqQ7moVMXX0NCA22+/HXa7HU6nE4sWLWpTbjp8/vnnuOWWW1BUVAS73Y6rrroKW7ZsabXP5s2bMWPGDNhsNgwcOBC//e1vO40vW86/VMWXLedfMvHt2rUL119/PZxOJwoKCjBv3jzs3bu3w3Jz6fh1J75sOX5A5zH+4x//aHMsWh51dXXtltur11DpY06dOiUFBQWyePFiOXjwoOzcuVNmzJghCxcubLXfAw88IM8//7zccccdMnHixKTKnjVrltx1111SW1ubeLjd7hRE0b5Uxrd48WIpLS2VzZs3y+7du+XKK6+UGTNmpCCK9iUTXywWk3Hjxsns2bOlqqpK1q1bJ0VFRbJkyZIOy77kkkvk8ccfb3X8fD5fqkNqJZXx3XDDDTJx4kT55JNPZNu2bVJWVia33XZbqkNqY8SIEbJgwQLZu3evfP7553LfffeJ1WqV2tpaERGprq4Wo9Eojz32mBw+fFi2bt0qo0aNkgcffLDDcrPh/BNJXXzZcP6JdB6f1+uVwsJC+clPfiIHDx6UmpoaWbhwoQwYMEAikUi75ebK8etufNly/EQ6jzEQCLQ6DrW1tTJv3jyZNWtWh+X25jW0zyUfK1askJKSEonH44ltn376qQCQw4cPt9n/0Ucf7VLy8ctf/rKXato9qYqvqalJDAaDvP7664ltBw4cEACyffv2Xql7MpKJb926daKqqpw+fTqxz/Lly8Vut0s4HG637EsuuUSeffbZlNU9GamKb//+/QJAdu3aldj2zjvviKIocurUqRRF09aZM2cEgHzwwQeJbR6PRwDIpk2bRERkyZIlMm3atFave+utt8RsNovH42m37Gw4/1IVX7acf8nEt2vXLgEgx48fT+zT0TWoRa4cv+7Ely3HTyS5GC9UV1cnBoNBVq1a1WHZvXkN7XO3XcLhMIxGY6tFbSwWCwDgww8/7HH5r7zyCoqKijBu3DgsWbIEgUCgx2V2Rariq6ysRDQaxezZsxPbRo0ahWHDhmH79u3dr3AXJRPf9u3bMX78eAwYMCCxz7x58+DxePDZZ591WP5TTz0Fl8uFyZMnY9myZZ02hfe2VMW3fft2OJ1OTJs2LbFt9uzZUFUVO3bsSEUoF+VyuVBeXo5Vq1bB7/cjFothxYoVKCkpwdSpUwGcew/MZnOr11ksFoRCIVRWVnZYfqbPv1TFly3nXzLxlZeXw+VyYeXKlYhEIggGg1i5ciVGjx6NSy+9tMPyc+H4dSe+bDl+QHIxXmjVqlWwWq343ve+12n5vXYN7ZUUJovU1NSIXq+Xp59+WsLhsDQ0NMjChQsFgDz55JNt9u9Ky8eKFStk/fr18umnn8rLL78sQ4YMkVtvvbWXI+hYquJ75ZVXxGg0ttl+xRVXyMMPP9wbVU9KMvHdddddMnfu3Fav8/v9AkDWrVvXbtnPPPOMbNmyRfbu3SvLly8Xp9Mpv/rVr1Iaz4VSFd8TTzwhI0eObLO9uLhY/vrXv/Z+IB04ceKETJ06VRRFEZ1OJ4MGDZI9e/Yknt+wYYOoqiqrV6+WWCwmJ0+elKuvvloAyOrVq9stNxvOP5HUxJct559I5/GJiOzbt0+GDx8uqqqKqqpSXl4ux44d67DcXDl+Il2PL5uOn0hyMZ5v9OjRcu+993Zabm9eQ3Om5eORRx5pt4NMy+PgwYMYO3YsXnrpJTzzzDOwWq0YOHAgLrvsMgwYMKDTJX47c/fdd2PevHkYP348br/9dqxatQpr167FkSNH+kR8qZQN8f3617/GtddeiwkTJmDx4sV45pln8NxzzyEcDveJ+FIp2fhEBPfffz9KSkqwbds27Ny5E9/5zndw0003oba2FgAwd+5cLFu2DIsXL4bJZMLIkSOxYMECAOjwPciG8y+V8aVSb8YXDAaxaNEizJw5E5988gk++ugjjBs3DjfeeCOCwWC7dciV49fd+FKtN2M83/bt23HgwAEsWrSo0zr06jW0WylLBtTV1cmBAwc6fFx4P/z06dPi9XrF5/OJqqqyZs2aNuV2peXjQj6fTwDI+vXru/X682U6vs2bNwsAaWxsbLV92LBh8qc//aknoYlI78b3u9/9rk1MX375pQDoMLu/UE1NjQCQgwcP5nx8K1euFKfT2WpbNBoVnU4n//nPf9IW37vvviuqqrbpSFhWViZLly5ttU3TNDl16pQEAoFEn5WdO3cmXadMnH+pii9bzr9k4nvhhRfa9FsKh8NitVrl1VdfTbpO2Xr8uhNfqo9fb8d4vp/97GcyadKkbtWpJ9dQfdfTlcwoLi5GcXFxl17Tcs/8xRdfhNlsxpw5c3q1TtXV1QCAQYMG9bisTMc3depUGAwGbN68GQsXLgQAHDp0CMePH0dFRUW3y23Rm/FVVFTgiSeeQF1dHUpKSgAAmzZtgt1ux5gxY5Iuv7q6GqqqJsroiUzHV1FRgaamJlRWVibu67733nvQNA3Tp0/vblgJycbXcg//wl/4qqpC07RW2xRFweDBgwEAr776KkpLSzFlypSk65SJ8y9V8WXL+ZdMfIFAAKqqQlGUVs8ritLmPehIth6/7sSX6uMHpOYz6vP5sGbNGixdurRbderRNbRb6U6We+6556SyslIOHTokzz//vFgsFvnzn//cap/Dhw9LVVWV3HPPPTJy5EipqqqSqqqqxK/TkydPSnl5uezYsUNERL744gt5/PHHZffu3XL06FF588035fLLL5drrrmmT8Qncm6o2LBhw+S9996T3bt3S0VFhVRUVKQ1NpHO42sZijp37lyprq6W9evXS3FxcauhqDt27JDy8nI5efKkiIh8/PHH8uyzz0p1dbUcOXJEXn75ZSkuLpY777yzT8Qncm6o7eTJk2XHjh3y4YcfyogRI9I+1PbMmTPicrnku9/9rlRXV8uhQ4fkN7/5jRgMBqmurk7s9/TTT8unn34qNTU18vjjj4vBYJC1a9cmns/W8y9V8Ylkx/mXTHwHDhwQk8kk9957r+zfv19qamrkRz/6kTgcDvnqq68uGl8uHb/uxCeSHccv2RhbvPDCC2I2m9u02Iik/hraJ5OPO+64QwoLC8VoNMqECRMuOnxo1qxZAqDN4+jRoyIicvToUQEgW7ZsERGR48ePyzXXXCOFhYViMpmkrKxMHnrooYyMU09FfCIiwWBQ7rvvPikoKBCr1Sq33nprYlx4OiUT37Fjx2T+/PlisVikqKhIHnzwQYlGo4nnt2zZ0ireyspKmT59ujgcDjGbzTJ69Gh58sknJRQKpSushFTEJyJSX18vt912m+Tn54vdbpef/vSn4vV60xFSK7t27ZK5c+dKYWGh2Gw2ufLKK9t0lP3Wt76VOBbTp09v83w2n3+piE8ke86/ZOLbuHGjzJw5UxwOhxQUFMh1113Xakhprh+/rsYnkj3HTyS5GEVEKioq5Ic//OFFy0j1NVQREelWewsRERFRN2Rv93oiIiLqk5h8EBERUVox+SAiIqK0YvJBREREacXkg4iIiNKKyQcRERGlFZMPIiIiSismH0RERJRWTD6IiIgorZh8EBERUVox+SAiIqK0YvJBREREafV/xRqGVf4QtKkAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "underused units\n"
     ]
    },
    {
     "data": {
      "image/png": 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OlZ8BJUeyUHwkE7L51tJdM3eGBg0aAAAO5tk6NHMch+CgBo6sUoWcnZ1vKVU4c2vUDZzh1q8JVD6G6xfkOCCoI7R+Ufi5z3c49ecFXCk2o9gqgYgQFRWlFOV5Hq+++iqKSopx9McdEDgeBo0ONM0FySP7Y0CH58Bx/91iOZ7Ho489huzsbJBtUtdK+/t06dIFrq6uFW67U7DHLswdg2RCybEs8AYV66h6lzKbzdBoNMprDw8PlJSUoLCw0IG1qtiaNWvQs2dPR1eDqQFxb/yOjqm2W6u3yCE3zICnRreCqLtzWzKAqt2/WfDB3HGkPDOKD2ZA38YHvObO6sTH3FiTJk1w6tQpR1ejUmq1GomJiXjmmWccXRWmhqWfy0PRkUw0fDAIvHDnP2ioyv37zr8azF1HcFGDd1KxwOMu9fbbb0MURWUm2rItIY7WoEEDPPfccyzwuEu4SDL0KQV3ReBRVeyKMHcc07k8qHxv8GyXuWMNHjwYH374Idzc3ADYZjUVRRFeXl7QaDQ1MqSVczEioFFjqNVq22uOUx77OTk5Yf369SAihISEVPuxmbqLrASPoRGOrkadxB67MHecon/ToWvJJq9jgPnz5+O9995TckbMmzcPsbGxAIB7720Hvf4oXouPRPCON7D57H68vP5dZGdnw0XtBGrFwWegD1RuKrzfoAjiP3Hw/3Q5AKDE4IyH3/0Y7q+/gOjoKHw8bx6cRdbSxtgjmVByJBO65p6OrkqtYH0+mLuaXGRByfFsaJu6g9ey0eRM5bKy/sLlyyvQsOFTcDa0QH5uHnQ6HVQ6WwtGbu5+WK25cHPrCJ6/szsLMjXDdC4PnMCVy+J8J2J9Ppi7Gq9XQRfpBfPFfBQfyQRZ62KWB6YucHfvhObNP4CLS0twAgcXd1cl8AAAV9doeHh0YYEHc8s0QS6QCiyYP2cegoODodVqERsbi127dlX6HovFgunTpyMkJARarRZRUVFYu3atXZmEhAS0a9cOzs7O8Pb2Rr9+/XDs2LGaPp1qw1o+mDsaWWWUHM0Cr1dBHewCjmePYhiGqV3Lli3D0KFDodVq7YZ9h4eH48svv0RMTIxd+f/973/49NNPIcuyXXl/f38sWrQIPXv2RPPmzXHp0iXk5OTYvTcsLAxz5szBQw89VKPnVBH22IVhriEXW2E+n1c6TQwAgHdSQ/TQskczDMPUqCZNmuD06dPKa1EUYbFYAAAGgwGnT59GfHw8VqxYoczaK4oiBEEAx3EQRREFBbZZv1UqFbZs2YIxY8bg0KFDSlbUsgRBwD///IPmzZvXwtn9hz12YZhr8DoR2nB36MLdoQ13hybMDYKrGpbUQhQfzULxsSyUnMiGVGhxdFUZhrmDmM1mnDp1Ci4uLnB2tiU/jGzeUtleWFiI2NhYLF++HMOGDcPPP/8MwDZKS5IkqFQqNG7cWClvsVjwwAMP4NChQ5g6dSratm2LwMBAu2NKkoStW7fWzgneItbywTBXkSTDnFIAudgKDspkuuB0IlS+BvBqNpqBYZiqOXv2rN0svkFBQTh37ly5ct7e3khLSwNgS0RX2jJiNBrLPVoBbDljLly4AMD2qOXEiRN221u0aIEDBw5U12ncFDaxHMPcAk7goQm0/4MhIlCxFeYL+SCLrXmTE3logl3AiazhkGGY68vKyrJ7XRowXOvKlSsYOXIkNm/erDx6AVBh4AEAFy9eROvWrbF//35U1IZw8OBBGAyGOjm1AMAeuzDMdXEcZ5vALsQIXVN36Jq6QxPkjOKDGY6uGsMw9YC7u7vd64r6aJRavHgx2rZtC29v75va9759++Dj41Pp9qKiohpJqlcdWPDBMFXEqQRoQowoPpyJkuPZysKG9DIMcy1/f/8qlf/xxx/xzjvv3HRn0dTUVPA8Xy7IKSXLMkJDQ6tUh9rAgg+GuQWCsxq6CA9ow9ygDXODprErig9nOrpaDMPUMWq1uspp9detW4cjR47cdPmOHTuWe7xT1smTJ5WOrHUFCz4YphpwIs/6gDAMU6G3335bmejwZiQlJV338cy1tm3bdsMyK1euvOn91Qb2ackw1cCSXgTRU+foajAMUwcNHjwYc+fOhUrluEy5AwYMcNixK3JbwcfMmTPBcRxefPFFALZevf/3f/+H8PBw6HQ6BAYG4oUXXkBubm511JVh6ixeI7I+HwzDVCo+Ph6//PJLufVarbbC8pP6PoNmDdpWy7GNRiP69OlTLfuqLrccfCQnJ+OTTz5BZGSksu7SpUu4dOkS3n//fRw8eBBLlizB2rVrMWrUqGqpLMPUVbyTCpbLhRUOeWMYhgFglyysVElJSYVlN13Yh9Scc9Crb7+1JCcnBz/88MNt76c63VKSsYKCArRu3RoLFy7EjBkzEB0djTlz5lRYdvny5Rg6dCgKCwshijdOK8KSjDH1lVRghulEDnQtPVn/D4ZhyjGbzdBoNDddXqPRQE0m5Jtv/9jh4eE4evTo7e/oOmo8vfrYsWPRq1cvdOvW7YZlSytRWeBhMpmQl5dntzBMfSQ4qaGL9ETRv+msBYRhmHLUavV183Jcy2QywcLffLByPceOHbNLXuZoVQ4+li1bhr179yIhIeGGZTMyMvDWW2/hmWeeqbRMQkICXF1dlaVhw4ZVrRLD1BmcwINT8YDEgg+GYcqbO3dulUa+SJLphmU4jrvhPkeMGFGnEo5VKfi4cOECxo0bh2+++abSTjKl8vLy0KtXL0REROCNN96otNzkyZORm5urLJWlnmWY+sB8IR+Ci4Y9dmEYpkKlI1+unQyurLLBhNXCgec4ZTbuskqTiy1duhQnTpxAgwYNKt1nVYbu1oYqfULu2bMHV65cQevWrSGKIkRRxNatWzFv3jyIoqg06eTn56Nnz55wdnbGypUrrzu8SKPRwMXFxW5hmPqo+FgWeIMKmiD2f5hhmMrFx8fj3LlzICIkJiYiMDAQarUaMTEx2LFjB+bNm4cGDRqA4zgYdS74adhHMGcU4anhw6BSqcBzPJx0BgwcOBCffvopEhISEBERgeLiYjz55JNISUmxzUtFhC5dumDcuHFYsmSJo0/bTpU6nObn55ebjW/EiBFo2rQpJk2ahBYtWiAvLw89evSARqPBb7/9Br1eX6UKsQ6nTH1VuDsV+lY+4ISKvqMwDMPcnm+//RbHjx+Hr2xE8zYtcW/fro6ukp0am9XW2dkZLVq0sFtnMBjg4eGhBB7du3dHUVERvv76a7sOpF5eXnXqeRPDVDd9lBeK/k2HodXNTQrFMAxTFU888YTyc+HuVAfW5PZV64PpvXv3YufOnThw4ACaNGkCPz8/ZWF9OZg7HacSIOirFM8zTL2zYMECBAcHQ6vVIjY2Frt27aq0rMViwfTp0xESEgKtVouoqCisXbu20vLXJq5k/jNo0CBwHKcs7p2CsPB/71VYtqioCJ07dwbP80p5lUqFGTNmKGU++ugjuLu72+3Tzc0Nx44dq50TojomNzeXAFBubq6jq8IwVWJKySfTxXxHV4NhasyyZctIrVbTF198Qa+99hppNBoCQBzHUUREBO3cudOu/MSJE8nf359+/vln+r//+z/S6/UEgABQo0aNaM2aNUrZXbt2UXBwMEVGRlLHjh2VcuPGjavls6x7XnjhBeV6hIeHKz8DoGCfQPpl5KdkyS5RysfExCi/l+joaBJFUSnv5OREL774Iv3www8UEhJCAQEBxPO83T5btmxJu3btqnI9q3L/vqUkYzWJ9flg6iPzpQJAIqgbOju6KgxTY2JjY9GuXTvce++9GDp0KIgIer0eQUFBOH78OLRaLU6cOAFvb9ujR39/f7z22ms4f/48Fi5cCLVajeDgYFitVhw5cgQcx2HHjh0IDQ1VEldOnDgRx48fh9lshqurK+Li4ipNYnm3cHJyQlFRERo0aIDLly9DkiS7XEIGrR6nTp+Gj58th4ggCJBlGeHh4UhLS0NeXp7SARUAXFxcMGrUKEyfPh0+Pj7Q6/XIyMhQ9icIArRaLY4dO4aAgICbrmeNJxljGMaelGNigQdzRzObzdizZw+6deuG2bNnw93dHWPGjEH//v3RqFEjeHp6gojwxRdfKO8xmUzQarX46quvwPM8pk+fjmbNmiE3NxePPPIIfHx88MEHHyiJK9u3b69MJd+sWbMqZQO9UxUUFKCw0DZ1g9VqVQZxlM3rUVhShMQFicrr0iDj/PnzcHJyUh6rlMrPz8fmzZsxduxYjBw50i7wAABJklBSUoK5c+fW2Hmx4INhblPx4UyoG7DAg7mzZWRkQJIkuLu7Y8+ePcjIyEC3bt3g4+ODtLQ0dOvWDa6urti+fbvynh49emD27NkoLi6G1WrFqVOnsGLFCly+fBk6nQ5ZWVlYt26dkrhy7Nix4HkeoaGhcHNzc+DZ1h3Hjx9Xfk5NTVUGcVx7fb5c+qXyc2kOkeLiYly6dAmSJNnl+SAinD9/Hn///bddsFg2SJEkCcuXL6/+E7qKBR8McxvIKoMTeQguakdXhWFqRU5OjnIzK5sq3MfHB5IkITX1v1EYc+fORWhoKHJyclBUVIT58+ejX79+ICL88MMPKCwsREZGBr755hv89NNP+P3330FE6NSpkyNOrc4rbdFo0qQJMjMzwXGcMnXJhYsXcOmILRXGmjVr4OnpCaDy5GLZ2dl444038M8//6Bly5bK/lu2bAlfX18AwNmzZ3Ho0KEaORcWfDDM7eA5kLnuzJfAMDXF09MTgiCUa6JPS0tTblbX8vLywk8//YTz58/j/vvvh8ViwXfffQeLxQKtVqs8OmjVqhWGDBmCCxcuoLi4GAsXLsTWrVtr/Jzqg7CwsHLrTp06BcAWLIiiqKSx+Gzux5BNEpo1a4b09HTlEVZlnnzySTRt2hQHDhxQ1v3777/K75jneezYsaO6TsUOCz4YpgqkQgtKTmaj+FgWio9loeR4NjRNjI6uFsPUOLVajTZt2mD37t0QBAE8z+Py5cvYtGkTOnTogLS0NAiCUGEg0rBhQ2zevBl5eXkIDAzE2LFj8cwzz8BoNKJx48aYPXu2XfnSb/gpKSmYO3cuBEGoU5Oi1SYnJycYDAa7PhtlWzNKSkqUxyV7zh9EwV8pyrbFixdfd9/e3t4YOHAgnJyc7NZbrVZotVoQETp06FBNZ3KNKo+lqWFsqC1zO+bPn09BQUGk0WgoJiam3NC/ssxmM7355pvUuHFj0mg0FBkZaTf0T5ZkMl8ppKKjmVR0NJOmT3idANAL//dCbZwKw9Q5y5YtI41GQ40bNyYPDw9q3rw5GY1GunTpEgUEBJAoitSlSxciIpJlmX5f8hstjv+Q9szfSJt/WkcPPPAANWrUiK5cuUIhISFkNBpp8uTJlJeXRzt27KAVK1ZQ8+bNqXfv3tS8eXNyd3en3r1704EDBxx74g5Wdqjt9RaDwUCF/16huaPfogc63k9ardZumG1Fi16vJ09Pzwq3DRkypEr1rMr9mwUfzB2jbA6CQ4cO0ejRo8loNFJaWlqF5UtzEPz666906tQpWrhwIWm1Wtq+cgsVHcmk4mNZZMkoIlmW7XIQsLwDzN0sMTGRPDw8lBvUmDFjaODAgaRWq4nneRo0aBA9+eST1KxxOPWL6EahHkEk8gJpRDU1bxRG8+bNo9atW5NWq6XAwEDKzs6223+XLl1o3Lhx1KVLFwoICGB/b1cNGDDghsEHz/PUvHlzCg5pTRx342DlRotGo6FDhw7ddB1Z8MHclWJiYmjs2LHKa0mSyN/fnxISEios7+fnR/Pnz7eVLbJQ0cEM6tu9N8UNecKuXH5+PoWGhtKGDRuUD0aGudslJiaSm5ubXZKxHTt2EJEtgPBy8aDHWvSkfa+spuHDh5Orq6tyU1Or1fToo49SSkpKpftnwYe9wYMH3zBYcHV1Ja1WS0EhYdSshe6G5f39/a+7neM4GjFixE3XsSr3b5YLmrkjlOYgmDx5srKO53l069bNbuhfWaU5CIgIJceyoIvygpOXK7Zt22ZXrjQHQbdu3ezSEzPM3Sw+Ph7x8fEVbtuyZQsAgCRCibkEwbOS8eKLL0J3/jiaRkTgkQmTwfPXn+urdB8MkJSUhO+///6G5dzd3VFUVITC3CycP10CcBxwnTyiaWlp190fXR2SWxNY8MHUSwsWLMB7772H1NRUREVFYerUqZAkyW7oH2Ab/nf48GFMnz4dS5cuRUpKCsLDwzFr1iwlB8G9He/Bd0u+wrdrlitj6vv164dZs2Zh37592Lt3L5KTkx1xmgxTr3ECB51OhzfeeMPRVanXJk6caJfRtDJnzpyp0n5vphNvdHR0lfZ5s1jwwdQrCxYswBtvvIGMjAw0atQIS5YswebNmxEXF1eurMViwd9//419+/Zh9+7dCA4OxkcffYSSkhL0798fv/76K6ZOnYrwiKbKezp16oTk5GRYLBZ07doVZrMZGzduhFarrc3TZBjmLlf6BevixYsOHenz1FNP1cyOb/kBVA1hfT6YisyfP1/pka3RaKh79+5Kh9LLly+Tv78/cRxHK1euVEaxGI1G5dllXFyc0qF07969NGDAAHp80BD69LXPqH1UrFKuf//+FBERQVeuXFHWCYKgLLj6HFQQBLJarY6+LAxz15o/fz65u7tfd2K7UmazmaZOnUpubm7EcRxxHFduYruyEhISan1iu7Ij9UJCQojjuHITvtX2wvN8lc6BdThl6oxrh77+73//KzcUtuyHSG0vHDgCoPTe9/X1pcmTJ9OJEycIAK1YsYIOHDigLG3btqWhQ4fe9UP/GMaRRowYYfd37OLiQqIokouLS7nRbWazmTp06GBX3s3NjQRBILVaTXv37qWFCxdSy5YtydnZmfR6vXLT12q1tRJ8XDtbcGk9dbobdxqtycXV1bVK58GCD8bh5s+fTwaDwaF/OFVZSuvq7e1NmZmZ1KtXL+rUqVO582KjXRjGccq2gAKg5s2b02OPPUYqlYo4jiODwaCMbittAS07yua+++6j6dOnkyiKxPM8+fj4UFxcHK1atYqGDx9OgC3vBcdxys2/Nv7eS0fqXRtUOXrx8vKq0nlU5f7NMpwy1S4pKQkvvPACCgsLHV2VSmk19n04SuuakJCA1157DQcPHsSyZcscUTWGYSqQlJSECRMm2GXjPHPmDBITE+Hp6amkGS8d3TZlyhR88sknSupxQRCwbds29O7dG3369IFWq0VGRga2bdsGX19fbN26FUajUekTBtxch8zbVTpST6vVYsmSJYiNjQUAu4ymjnIzKdpvFQs+mGq1YMECxMXFVTqZUV1RYioBAPAcD57jlRkif/jhB6xevRq///47GjRoUO59W7ZswZw5c2qzqgzDAJg9ezZGjhyJc+fOKev0ej2WLFmCBx98EBqNBiaTSZnY7quvvsKrr74KwBZ4qFQqaDQaTJ06FdnZ2SgqKoIkSbh8+TLi4uLwxBNPIC8vDyqVCn379lXeV9NKZwv+7bffAADdu3cHgJsa3VIbRo4cWSP7ZcEHU22SkpIwfvz4ejUHg0wytBoD9Ho9AGDnzp3YvHkzGjVq5OCaMQxTqrR1oF27dnY35Xbt2mH79u3w8fEBEdl96SnN49OjRw/o9XrwPI/CwkLly0UpSZLQuXNnzJkzB7Isw2Qy4YUXXoDBYFAmvqsNx44dAxEhMDCw1o55M5599tka2S8LPpjrWrBgAYKDg6HVahEbG4tdu3ZVWvZmx6LXNUUl+UhJsU3GlJOTA71ej9TUVKSmpqK4uNjBtWMYprR1oHSaeMD2WEKj0SgtHaVfekontivN4zNu3Dh07NgRRUVFyntdXFyUxxqiKKJ169Z223Nzc1FYWIjCwsIan9jO09MTPM8rgVNd+uJjNBprbKgtCz6YSpU+Y502bRr27t2LqKgo9OjRA1euXClX9ptvvsH58+drpZmyJsmyjAYNGsDPzw9+fn5ISkpydJUYhrnKaDQqrREuLi7KI5jU1FSYzWa7WVjnzp2L0NBQdOzYERs3bkSTJk3wxBNPQK1SY9SoUUrwMXToUOWxK2ALasq2eHAch71799bYZ5tarUZkZCQAW1bm/Px8qNXqGjlWVTVt2vTGhW5V1fvl1iw22qXuqMpcKa1atSIANGrUKIf30K6OZfjw4bV4pRmGuR6TyUSCINDKlSspJiaGXF1died54jiOwsPDSavVEmDLAZSamkpPPvkkNW/enF555RUqLi6mVatWUUJCArVt2ZFcdB4kiirlb53neWUpu640t09cXFyNn9/XX3+tjLZ74oknKCIiwuGfgYIgkL+/f5XOgw21ZSpUlenmCwoKlD9CwDbkbM6cOTRs2DDq06cPERFt3bqVevfuTX5+fsp/2NLEXo5OjnPd5eowurKLk5MTG0LLMHVYTEwMxcfH07Jly5ShsmX/hnmep19//ZWefPJJ0uv1pNfraWhcHM1dMotaNDeSXmVfXqfT0c8//0wHDhygUaNG0eLFi6lly5bUq1cv5UtUbeX5ICIKCgpSgqjGjRuTRqOp1s+4qi6enp7UoUOHKp0DG2rLlFOVRygAlKFmjz32GNauXYvWrVvjxRdfRHFxsfKMtbCwEFFRUXjrrbeU9wmCAH9//7o92uWafine3t546qmn2CgWhqnDJkyYgM8++wwlJSWYNGkSRNE2OwjHcYiIiED37t3x559/4szhU9BDg46NW0N78Sz+/OwbXD6ajyKL7TNJ4EU8+uijOHnyJPr06YMWLVqAiPDGG2/g4MGD2Lx5M86ePYvIyEg8++yztfa5MGvWLBARhg4diuLiYpjN5lvfWRX73pV9zKTRaMDzPPLy8jB27Nhbr8ON3FqMVnNYy0fNqOp086IoEgB66aWXlNYSjuPIaDRSTEyMXdmUlBQCbFkGy6Y0r8uLWq0mo9FI/fv3r9HrzjBM9UlMTKTAwEBSq9UUExNDO3bsULZ16dKFhg8fTnlbLtCFSX/Q90PmUbCbP4k8Twa1iu719aLZDz1P//5+odL9OzqJ4LXn99JLL5Gzs/NNfaY5OTmR6jrbRaFqrSEcx1V5Comq3L85oro1PCEvLw+urq7Izc2Fi4uLo6tzRzCbzdDr9fjhhx/Qr18/Zf3w4cORk5ODn3/+uVx5jUYDwNYT/NNPP0VsbCzat2+P/Px89OjRA2vXri1X3svLC+np6XjhhReQlZWFr7/+ulbOryqGDx+OJUuWOLoaDMPUEEtqIdLm7AUA8HoRmhAjNCFG6CM9wetVDq7drRk4cCBWrlxZbsSNt4sBV/IKYTC6oUFwMM6ePAbe4IvijPOAZFXK8RwAcPD19UVBYSHy8vKue7x27drhiy++QIsWLapUz6rcv9mstneB0mFqFU03f/ToUbt1JBNOHDwPwNac2TAgCF1a98KO7X+isNA2FM1isiIvNw9qjRqiKCpNdhkZGejatSt++OEH5dFMdeMBVPZAx8vLCy+99BLWrFmD6Oho9hiFYe5Corcerg83gsrPAE1jIzjB8ZlCb9fy5csB2B6fDx8+HB999BH0hbn47udV2LJrD44dPQIfHx/0GfgYtl7k4P3UPHwv/Axr6k9IyefRyGMUzuX5YeGlFThz7izOnTsHo9FY4bHuu+8+REdHVznwqCoWfDDIzyrBhSNZuHQwAwUnc5GWYQsciAhnzp1Ck1a+8HTygV5lQIEpD5mncvHz9HVYuOE9GJ1dMeCBR5TymzZtAsdxUIkqmGXbM0uNWgOT2QQOHAgElSDAUiaC5zkOKkEArxXgxImAmkdhoYSikiJlu0wEgQf0akAStGgV3QZ//fWX3Xmkp6fjwIEDtXHJGIapozieg3Pn8tmJ7wSDBw9Geno63njjDaSmpiI6Ohrr1q9XvljmpWege4A/ZjQNhOHok9he3BKvbf4A53Pfh16lQ6/+vfHVN19XGnjUJhZ83GHIKkPKNcGaXQJIBALgotZCEASkpaX9V04mXD6XAjFfi7VTt4PjAIO3Hr4d/dAyJBT8l7akN/fe0xl//b0N6fmp4DgOgiAgx5yPdEmGVUNQeegQ81gXYAaUxy5EBLPFrCTmMZlNpUcFB1vrhYrjYSFbG4ZMBG+Ow0suHni/IBdpOfmQZAAcIOgFOEc5w2egDy58fAH5x4oAlJQLPEp169atxpLiMAzDOFp8fDzi4+Mr3LZlyxblZ9ksoetKb3QIjAbvpILgpoH3c9Hg+Ou3BJXdR01iwUc9RkQwnc4FWWQocxAJPARXNTTBruBE2+MQKc+MVs2jsO6HX9GzWWdbbyJZxu9/bkGbhg+jxKjBwMntoDX89zw0MjIS+/fvx/Ydf+Pzzz9HdHQ02rRpA1mWYbVkg1K/xeAQP4ADNsx8HQDgLnDI5nlIsgxwHGRZulolHrP7dUfk+St4/eRp9Pb2RksXV/TanQw9z4MArAxuBD3Po+eQRgh3OgDyboYSvTsuRj4K16aPwCyZIY+UoRW18NZ7195FZhiGqYd4tQC3x0Lh+nAjCM5qlBzLumHgUZtY8FGPSVklEJxUUPkYrltOcFHjf69OxPDhw9H+wXsQExODOXPmoLC4CO3De0DvosEzz41CQEAAEhISAAB9+/bF/v37ERISAlEU0bt3b9vjFJUKVsmMZckH4RsciC4xbZWU6mcysnBf+xhENG6MdX/9jaycXFvGvsJCWEQBH5vNePmppxBgdENBcRGwOxlFV4fkXrj/fnQICYH70DjA3x8cAB2A0Jq8gAzDMHcwTuAhONeNbKnXYsFHPUUSwXQ2D/rWN9cKUPqscOrUqcqzwrVr1+JAkgmNojxx/rfzdmO977nnHgC2yY6GDRsGDw8PrFy5EkOGDAEA5Jms8FBp8PLM95X3mK1WbPx7B/5I3oNe93TDhLjR6BkfB54X0MA5HH94leCFlStx+fJluLq6AgD+7//+D4mJiWjyf/HwqeEOTgzDMEzdwIKPekg2Syg5nAl9pKcyP8HNqOhZ4eEV2yBZ5XLP+SIiIgDY5h349NNPldYSSZKg0fB476GnsOjgXxjdYzAmdBkGfY4BQ79/GSczzuLDXq9C4AWMeXUiikqKIfIiOnn2Q5v7+8C3bxucPHkSANCqVSts3LgRUVFRbFg1wzDMXYQFH/WQ+UwudC09wQm3n6CW5znI0n+pXgYNGoQVK1Yo48nNZrPSgdNgMOD+++/HxX0nEO1+P9JSfkLyoX+xZMOPsMj/jSl/PGm88nNoSAhOnj6NoFn3Qa5gkOyRI0cAAFOnTmX5NxiGYe4SLL16PVUdgQdgy+Wx+7ez+PaNHejZYbBtPPk1MYKzwQgAiGzSARs3bISH3gM8J6CpfxNczk9HaW9XgbPVyVljAAcOwe4BOHnqNIhIaaEpnRlSp9MBAKKiouDk5ITWrVtXy/kwDMMwdR8LPu5yHR9tguhuDREY4YHNu1cC4MALPAJ8gsDztkAh2D8EHMfDZC60zdlytaFk/ZFtAABPgxucNQbcH9YRHIASiwkt/MKQXpANulpYr9Yi0KeBMnV0SUkJvL29kZubi+7du2PXrl21feoMwzCMg7Dgox4hiVB8LAuCm7ba9tmkjTc6PRaK6If9YLFaEBnZEharBUOeHKgMlT1+/iACAvxx5Ox+iCoRnIaHUyd/FHG2/B3N2rZAvqkQxZ62UINXCTiSfgqi7r+hu0FGf6SkX1Zyjbi4uCA9PR0tW7bE1q1b0bVr12o7J4ZhGKZuY8FHPSEXWVB8IB3axq5Qeeurff+HDh0CAISFhQGwJQwDAK1WC5PJhJSUFJhMJgwcOBC5hXngtCL8/PzAcRw2b94MAEriL5PJBKvVitzcXERFRUGtVuNg2glIsoRLly4BAHJzc0FE+OWXX5CZmVmljrMMwzBM/caCj3pALrGi5GQOdFFe4FRCjRwjJycHgK1TaVl6vR48z6Nt27bQ6XTw9/cHyQCvFfDss89WuC93d3fwPI8WLVrg5MmTFU4N7e/vD47j0KVLF7i7u7Pgg2EY5i7Cgo86zpJWCPO5PNvolhq8QTdu3BiArS8GYJsnRRAElJSUQBAEZGZmwtnZGWmXU+Gld0POhvOYPGkyBF6ARqVBaMMmCAloDFEQkZWVhUEPDsTBgwdRWFgIAODA4f52neHm5gae55GWloYHHngA27dvx/jx45XkZgzDMEwNqGNf8FjwUddxHMgqQ8631OhhgoKCAADbt2+HwWDAunXr0KpVKxQVFcHV1RVnz55FZGQkNm3ejDYBzcGZbXO2uGldwBFgsKqgt4rwNXgAAIS04v9OARwAAkwacBwHDw8PSJIEQRBARBAEwdaRlWEYhrkrcFSaG7uOyMvLg6urK3Jzc1niqTLMF/Ih5ZmhCjBANFZfh9OyfH19kZaWhoiICBw+fBg6nQ7FxcXQ6/UoKiqCXq+HyWSCl7sP9KIR59OPw2q1Qmt0Q0lONvz9/HHpsq1PhyAIMLq6ITMrAwBg0DmjqKQAnp6eSE9PB8/zICI0adIE2dnZGDlyJGbNmlUj58UwDHO3KzmeDW2YW40eoyr3b9byUU+oGzpD19wDcoEFxYcyQFL1x4xz584Fz/NK4q/i4mLlX0EQUFxcDJ1Oh/yCfBSa8uDsZMtRV5KTDQBK4AEAsixDrVEpc8MUFueDiJCenq5sBwCLxYJnn30Wb731VrWfD8MwDFM3seCjnlE3cIY2zB0lRzJhSS+q1n0PHjwYc+fORcOGDaFWqxETE4MdO3bYZrK1WtG5c2c8+uij+GHO3/h06ios+94PTwz3hNrfD1Br4KXRYIjRiONvvQVZlnHp0iXs27cPY8eOhZebH9QqDRo3bozXXnsNJpMJsizjzJkzmDFjBtTqujn5EcMwDFP92GOXesycUgAppwSihw5EACQZnMhDcNeCV9fMqBgAWPTSn7CaJfR9qQUun5wJ09oj8GsbD6dOtiRjvFoFcLbsqRxv+3fDokNwctOg+9Ns8jiGYZjaVtceu7C5XeoxdYATyNcAKd8MnucAwdY51Xw+H3KxFbqmbjUyNLek0Nb59ceZ/wJ42LZsAbBlz3Xf17xzQLXXhWEYhql/WPBRz3ECB9GosVsnumpAEqHkWBYEVw3UAU7Vesy4N9sjO7UQTu5agABZJhARQABd/Zlk2P4lKK99gllLFsMwDMOCjzsWJ3DQRXjAklqI4mNZ0Ia5VVueEKOPHkaf6s+yyjAMw9wdWIfTO5zK1wBNkAuKD2RAyi+faZRhGIZhahsLPu4CvFaEPtIL5vP5jq4KwzAMw7DHLneNgyuApI8BYSegMthS7XI8bMNSUOZnrvKfwQEkAxpn4IllgHtjR54RwzAMU0/dVvAxc+ZMTJ48GePGjcOcOXMAAJ9++im+/fZb7N27F/n5+cjOzobRaKyGqjK3xacFABnwbw20fAy2sbmEqz1Dr/589TVsnUcr3J51Gjj4A5BzgQUfDMMwzC255eAjOTkZn3zyCSIjI+3WFxUVoWfPnujZsycmT5582xVkqolXGDhYQW5h4DqMvfX9pB+3BR+CqvrqxjAMw9xVbin4KCgoQFxcHD777DPMmDHDbtuLL74IANiyZcvt1o2pTqZ8EARwJ9fc3n7kqxPcCSwjKcMwDHNrbqnD6dixY9GrVy9069bttitgMpmQl5dntzA14OQmABzwRNLt7Ue6OmKGtXwwDMMwt6jKLR/Lli3D3r17kZycXC0VSEhIwJtvvlkt+2IqkXoQJT8ugKqhDxDU8fb2JV1t+eBZ8MEwDMPcmiq1fFy4cAHjxo3DN998A622eqZ1nzx5MnJzc5XlwoUL1bLfu8mCBQsQHBwMrVaL2NhY7Nq1y77AhR2QLSLE3v+DxWLB9OnTERISAq1Wi6ioKKxdu9au+EcffYTIyEi4uLjAxcUFHTp0wJo1Vx/XSOyxy53mhv9/yriZ/z9lzZw5ExzHKY9jGYZhAABUBStXriQAJAiCsgAgjuNIEASyWq1K2d9//50AUHZ2dlUOQbm5uQSAcnNzq/S+u9WyZctIrVbTF198QYcOHaLRo0eT0WiktLS0/woVpFPRlB5EW9+liRMnkr+/P/3666906tQpWrhwIWm1Wtq7d69SfNWqVfTrr7/S8ePH6dixY/Tqq6+SSqWigwcPEp3cTDTNhSjrTO2fLFPtSv//xMXFkZ+fH3EcRwBIFEWKiYmhnTt32pUv/f8TFxdHDRs2JJ7nlfKRkZG0Zs0apeyuXbsoODiYfH19CQB17NiRANC4ceNq+SwZhik+llXjx6jK/btKwUdeXh4dOHDAbmnbti0NHTqUDhw4YFeWBR+1IyYmhsaOHau8liSJ/P39KSEhwbZClkla9QoVvdGL6Mox8vPzo/nz59vtY8CAARQXF3fd47i5udHnn39OdGydLfjITan2c2Fqx8CBA+2+OIiiSADI29tbCT4AKIGFk5OTUr400ABALi4upNFo7N5T9r2CIFBkZCSpVCpydXUltVpNAMjPz48FIQxTy+pa8FGlPh/Ozs5o0cJ+SnSDwQAPDw9lfWpqKlJTU3Hy5EkAwIEDB+Ds7IzAwEC4u7tXqVWGuT6z2Yw9e/bYDWnmeR7dunTC9o2rQK2KYf7nIKR8M3TduwFeYTCZTOUemel0Omzbtq3CY0iShOXLl6OwsBAdOnQA5DO2DeyxS7103333YevWrcprIoLVagUAXLlyxa6sLMsAbKPbyiotf73O4aXv/ffffwEAubm5yrbLly8DABYtWoTc3FwsWbLELlcQwzB3vmpPr/7xxx+jVatWGD16NACgc+fOaNWqFVatWlXdh7rrZWRkQJIk+Pj42Fac3wnLp0/C4+xOXDpyEKbkfVA1CYR+2Dhw94wDAPTo0QOzZ8/GiRMnIMsyNmzYgBUrVig3hFIHDhyAk5MTNBoNxowZg5UrVyIiIqJMh1OhNk+VqQZJSUlK4NG6dWsH18YW1CxZsgT+/v6OrgrDMLXsttOrX5vP44033sAbb7xxu7tlqiLtMOSfV8C05whELx3EsCjwpvPQvvoTwNvHl3PnzsXo0aPRtGlTcByHkJAQjBgxAl988YVdufDwcOzfvx+5ubn44YcfMHz4cGzduhURsu1bLxvtUv+89957AIDg4GDs3bvXwbX5z6VLl3D69GlHV4NhmFrEJparxzy1BIHncP7beTAfOQntffdC9dw3SCM3+DYIKhd4AICXlxd++uknFBYW4ty5czh69CicnJzQuLF9qnS1Wo0mTZqgTZs2SEhIQFRUFObOnQuUBh8sz0e9UvqIDgDOnj3r2MpU4JdffoGPjw+efPLJciNpKhthU3YkzXVHaDEMU+ewieXqI8kCHF8L+vkjtPZ3wTZNMAZP/BHgeciyjE2bNiE+Pv66u9BqtQgICIDFYsGPP/6IQYMGXbe8LMswmUxlHruw/zr1yaJFixxdhRu6cuUKvv76a7z00ksoKSnBp59+ioceekjZPnToUEyZMgUvvfSS3fq5c+cqP3ft2hX33HMPFi5ciIcffhh6vR6RkZGYOnWq3XsYhnEsdgepT64cBe39BqY9/4BKiqBq6IOXpidg+HPj0bbbV4iJicGcOXNQWFiIESNGAACGDRuGgIAAJCQkAAB27tyJlJQUREdHIyUlBW+88QZkWcbEiROVw0yePBkPPfQQAgMDkZ+fj2+//RZbtmzBunXrAPkiAI71+agjFixYgPfeew+pqamIiopCYmIiYmJiym0/d+6cA2tZNR988EGF67/++mvk5OTgzz//rPS9mzZtQv/+/bFkyRI88cQTePnll1FUVIS+ffti3759aN68eU1Vm2GYKmDBRz0hr5sO07a/wGnU0ES3BNd2CODbEoMBpBdKmDp1KlJTUxEdHY21a9cqnVDPnz8Pvszjl5KSEkyZMgWnT5+Gk5MTHn74YXz11Vd2Mw9fuXIFw4YNw+XLl+Hq6orIyEisW7cODz74ILDrM9bqUUckJSVhwoQJ+PjjjxEbG4vRo0ejffv2UKvViIqKQp8+fTBt2rR6O6u0RqNBYGAgTpw4AR8fH6SlpWH16tUAAFEUodPp4OPjg1OnToGIlPeNHz8egiDAZDLB09MTzz77LD766CPs2LGDBR8MU0ewu0h9kJ8G07a/oW0TCq73B4CosdscHx9f6WOWazsEd+nSBYcPH77u4a7bRC9bWX+POmL27NkYPXo0RowYgaSkJOzevRuurq546qmnUFhYiNdffx3Af8Ne6wv+6uPDRo0aKS026enpynY3Nzfk5+cjPz8fKpUKrq6uyM3NVQIQq9UKrVaLPn36ID4+Hnl5ef8NFWcYpk5gHU7rA70HRE8NrBczygUetU6ysJaPOqC0A2np5I6lgUifPn1w+vRpzJs3D2RLIqgEIfVFabB09OhRdO3aFRzH2QVQ+fn5Sh+lrKws5OTkKIEHx3FISkrCoEGD8P3338NqtWLatGn/DRVnGKZOYMFHfSCZwalUsCWPdDDZyoKPOqBsjpeygYiPj4+S6A+wtRKMHTsWgiBApaofLVYqlQqCYOtTtHr1artHKoAt8d23335b4XsFQUDz5s2RmJiI0NBQcByHuLg4DB8+/IYtfgzD1B4WfNR1Oedhnj8E1iv5UPV+wdG1YcFHHVQu2RyAtLQ0ALa+EWq1Gq1bt4bFYnFUFW+KyugOjuchyQRJkiotl7B2E7ROThVus1qtaN68OZycnHD69Gk88MAD+Oyzz/4bKs4wTJ3Ago86Tlr9FsgEaMfOA4I73fJ+qm3m0qt9PlheBcfy9PSEIAhKkFEqLS0Nvr6+5coPGzastqp2yyxFhSBZhixLEBqHQtUiGryvP8TYe+xy1rzS4wGUFBVDfe8DAAC1Xg+DwQBBEMBxHLy8vDBs2DBIkoTk5GQcPnz4v6HiDMPUCSz4qMvyLsN87DzU9/cCvMJveTeloyKmTZuGvXv3IioqCj169Cg3l0epKVOm4JNPPkFiYiIOHz6MMWPGoH///ti3b9/VPh8CGjRogJkzZ2LPnj3YvXs3HnjgAfTt2xeHDh265XoyN0+tVqNNmzbYtGmTEohcvnwZmzZtQocOHZRWkNJ5WDp27OjI6t4c89XggAjS6ZOgi1egF3WQdv0FXO3zIahEBEU2Q4uenaE+cQCArY+IJEmQJAlEhMzMTBw4cABffvklmjVrhri4OGzZsgVxcXGOOjOGYa5VgxPc3RI2q20ZVguVvPMIScvH3dZubjjz7TWuO/PtuilEc1tV+D5l5lumVixbtow0Gg0tWbKEWrZsSc2bNyej0UipqalUXFyszDC7ZMkSWr9+fbmZZ+viIqi15BTZgziNwX6bSkW8pxe5vjOXOBdXQgUz6ZbOvNujRw8KCgoitVpNKpWK/Pz8aP369Y7+dTGMQxUfzazxY9TYrLZMLcs8CbnYDM7JeMu7qHTm227dsH379grfc92Zb4c2LNfno9zMt0ytGDx4MNLT0zF16lSkpKRAlmVMmTIFWVlZmDp1qlJuwoQJyMrKcmBNb8zV1RWFBQV4elQrrF69BQVXH5HwPKDViwhs5o12nRqite8mfB2ux7/782GxEDgOADi4uLjAaDTi//7v//Doo48qyfFmzZqFpUuX2nLUMMzdzPbHUmewxy51Uc4FYPdiWJa9At6gAtd10i3vqqLOiACUUREVue7Mt2XyfFQ68y1Ta+Lj43Hu3DlYrVbMmzcPS5cuRXR0NPbv34+33noLoiiC4zhwZT54uCp+CNXEN5SQkBAkJiYiMDAQarUa4eHhGP7UU2jUqB2WLAlAZEtvdO8ege3bFyD1UhZmv/kZdq3JxivPrcOZUyYMGDAQR44cwcKFH2HFihXIyclB165dkZiYiPDwcHTt2hXJycn/JcdjGKZO4YiuGcfmYHl5eUrSIBcXF0dXp3ZYTcC5v0HHN8F85CTk7HSA4yH6+ULVKx4IjL3lXV+6dAkBAQF46aWX8MMPPyhpuMPCwnD8+HHs3Lmzwvd07doVR48eBWDrX9C9e3ds3LgRxd8/C1zaiz+azcCsWbOwe/duXLlyBQMGDMAff/xhm/mWBSB1xvz585X06w0bNsTp06fB8/x1R5OUxXFAdX9CvP/++3jppZfKrf/+++9vaThs27Zt0bt37+qoGsPcsUqOZ0Mb5lajx6jK/ZsFHzWIZIJcYIZUYAFk+q/Zq/QfngNtfgfSiX2A1QQOFqj54+BFCQhsD+jcAY4vv4BsdwSSK/4ZV18TwWyVoB2WBIHn8OmotogNccOcNcex9M9z6BAWgLEPvwuAA8fJ4DmA52V8uWUZth76C8/1HAajwRlnr5zHR+u+gY+LB75+dgKC3M/jeMtH8Ndff6FNmzYYMGAAVq5cifnz5yMkJASffPKJQ643c2Olwcj58+cr3M6reMgW2TZ9j46HzqpGkcUMIvssqaX/la+m9qpShDJ8+HAsWbKk3Pq8vDykpKQoLTMVtdZUtM7f3x96vf6mj88wd6O6FnywPh+3iYgg5ZhgTS/+L8ti6UaOA++kguCsBvgyH9ClXeRAgNEZqnAPcJCvBhH+AEm24MGUB8iSEkjY/pWuBiCc7Q7A8cqxyq/noOY46NUCGns7YcR9IQDHY+Eodyzaeg4myYCsIneE+Z4CyRxkmYNMwNZD2zC440Po0KQFZOLR2CMQn2/8HqKgxpGcGGSLEXj0oYfKzRLKhjPWfaWp+E0mE5566in8uvZXFBYUokF4A/Se0Bu+zXyRZ87Dqv/7CVFuzTCh00h86XIKy7SukD98FUWXM6DTcYgMbYaezaYiun04Og0MhdFbX+njnMWLF+Opp566Yd1Kh20zDHPnY8HHLbCkF8GaWaJEGaJRA00TIzj+Fjr0PPxK9VbuGmazGcXDdDhyuRBLzT2VmW8FUYSs84KTlysWn9xhN/Otdd4kIMQNzUZ3VWa+FdUioOfRtIMvctKK7Wa+BYCvvvrqv5lvmTpPo9Fg5syZeOaZZxASEqL8Hku99+97AGxDdbM3bEBfnkPRnPcgyxIsmWp4u0QjIrYhfBu5Ku+pY42otWbBggWYOnWqXadelUoFjuMQHR1tN9OwxWLBjBkzkJiYiOzsbKV8ad+cZs2aYdasWejZsyc++ugjvPnmm0ouF19fX/Ts2RNLlizBuHHjMGfOnFo9T4apTiz4qAKyyCg+kgmVnwG6pu6Ors5NycjIgCzLePHFF+1mvh00aBD27DgAlUYoN/Ntu3btsGjRInz++edwdnZGq1atIEmS7UPw6tOjsjPfAsDJkydZ5756JigoCEFBQdctI4piuRYu5j9JSUl48cUXIUkSOI5T+tNYLBbodDqEhYWhR48eOHbsGLy9vTFlyhQsXLgQFosFWq1WKWu1WiGKInr16oX+/fvj77//xqZNm5CRkaEcKycnB0uWLEFYWJgDz5hhqgcb7XITiAjmi/koOZYFXXNPqLzq3/Plxx57DOfOnYPJZMLOnTvh7+8PyARRzWPLli12z+C/++47PPTQQ5AkCbm5ubhw4QJGjhx59YOVwAscFi1ahLNnzyqPWd58800WeDB3ndmzZ8Pd3R3Ozs7gOA6BgYHQarVQqVQoLi5GYGAg9Ho9vvjiCwC2FkKe50FE0Gg0cHZ2RrNmzeDm5gZJkrB//348/PDDmDVrFv766y8YjUaEh4fD09NTaVkym82OPGWmvqpjLZMs+LgOkgjFR7NQcjQLgrMauhae4IS6NVb6RipKw71gwQIsXLgQx84exNjp98PH6AKtWoXWYY3w23uvQUpeh0/HPoGza5Yh+bvP0L9LB3z91ZcwmUx4fPw9GPlG9/Jp169KSEhAu3bt4OzsDG9vb/Tr1w/Hjh2r7dNmmBpXmkMnPT0deXl5ePDBB3H+/Hm0b98e3t7e4HkeK1eutMupYzKZlNaOXr16AbD1dTGbzeB5Hn/88Qd0Oh1Wr14NNzc3PPnkk/D19UVhYWGFafMZ5qaxPB/1h/lCHlQ+euiaeUBwdfBU9reobBpu4L9U6yqVCp0bueNKQT4KivKxIU6Nts4piJv6Dvjfn4P3X6PR8O+nsWzOGHy17EvoqQBR3oBszkFBUTaWL1+upF0va+vWrRg7dix27NiBDRs2wGKxoHv37igsLHTE6TNMjSnNoVPaItG6dWtIkgR/f3/Isgy1Wo3Lly/b5dTp0aMHBEEAEWHDhg0IDQ3Frl27UFhYCEmSUFhYqCTsK52R948//kBxcTEuXLgAURTh5eXlyNNmmGrBgo/rUAe5QMo3o/hYFooPZkAusTq6SrdkwoQJ+Oyzz7B06VK8/fbbaNKkCQAgz2rFmG6hIFGH10+3w/w/c6B388OUjMfwbcC7+Oe+Ffj8sB4694bQuPghxeyKNx8JRe9oP3zzzTfo0KGDMmfImTNnsH//fnz66ad46qmn0Lx5c0RFRWHJkiU4f/489uzZ48hLwDA1zmg02r0WBKHcTMJz585V/mbS09Oxc+fOch11S/tffffdd7hy5cp/o+g4jg0pZu4YLPi4Do7joAl0gS7cHdrmHjCfz4clrf59gx88eDDef/99vP766zhw4AAsFgt++eUX/HsxDw9GB8LFxQWnz5yGWq9HtwcfxKHjxzHjw7mI7dkL2bm58PLzx9/JuyFxPJxcnaHXqrBlyxa0atUKmzdvBmALcFq1amWX1hsAcnNzAQDu7vWjgy7D3KzSR5qlzGYzBEHApUuXlBl2VSqV3UzDXl5eWLNmDc6fP49u3bqB53klA61arQYAlJSUAACioqKURzOAbRqDvLw8JCcnY968eRBF8aaTxTFMXcOCj5vEcRy0YW62Ibb1UHx8PHbs2AEAWLp0KRo3bgxJJvi4u2DYsGHw8/MDYEu7brVacfjwYZSUlODxxx9HXl4eCgsL0b17d0xfeQQ/7rqA7OxsrF+/HjqdDmq1GkQEIrLruFo6yqZTp05o0aKFI06bYWpM6SPN0scg27dvR5s2bZCcnIzc3FyYTCb4+voqMw2X1bBhQ2zYsAE5OTkIDLR9AeA4Du7u7mjQoAEGDBiAFStW4JtvvkFISAhcXFzQuXNnGAwGaDQaxMXFYf/+/XbBD8PUJyz4qAKyynWux/DNWrBggZJrYNSoUdi3bx8AwHrxEMhUUu685syZAx8fH3z33Xc4fPgwwsLC8P333yOz0IwSiwSz2YxBgwZBEASYzWZ06NABzz77LEJCQpTOqI888ggOHjyIZcuWlavPzJkzwXEcXnzxxRo/d4apKRMmTEBOTg4AYM2aNcjIyEBhYSEKCwthsViQlpaGy5cvY8mSJZg8eTLuu6cT/Bs2hH7wcOgHPgljeDNcuHgRhUVFMFss4LU6mHkBixYtwq5du9CgQQN4enpCq9WiqKgIhYWF0Ov18PDwYAE9UzV17d5VA7Pq3paqTMlbm2SrTIV700i2yo6uSpUtW7aM1Go1ffrppyQIAj344INkNBqJB2iefwD1dXGh+52c6EhEOPU1ulBznYZEDiQANKmxD00P8yeNwJHIg0695E2D7g0lUaMno38jahzbnTz9A6ljx47EcRwtXbqUTp06RV26dCEA9Msvv5Srz65duyg4OJgiIyNp3LhxtX9BGKYaJSYmksFgKM1bTACI4zgCQE5OTuTu7k5arZYCAgLIx8eHRLXarqyycBxp7u9Bnt+vIyKiyMhI8vHxUfbn7OxMHMexvxvmlhQfzazxY1Tl/s1aPm6S6WR2vRxqC9hyEYwePRqjR49GmzZtEBYWBr1eD2+NGnsMKiTzhHvvjYLnoC7YJVmhMxqgFUUMaxaIFzq2wGOcC/o1DQA4Dh8cNGLTkWxYTcVo+9hYXDp5EJqwTjhz5gwaNGiAY8eOKTPidu/evVyrR0FBAeLi4vDZZ5/Bza1m5xlgmNoQHx+PgoICu1l627Vrhx07diA/Px+ZmZmIjY1F06ZNMWbMGEyfOQZuH34GIagRoFKDczFC+2AveCatReTbs/FstG1ixrZt20Kr1UKtVsPT0xMxMTFYt24d/vnnH5bdlKkSIqpzQ23ZxHI3yXwxH7xWhOipc3RVqsRsNkOv1+OHH35Av379kJSUhOHDh6Nt27ZI27cPp4uLodXpsHbtWnz99ddYvHgxunTpgo0bN6J169ZoFh6Oxps243NJhqDTKL+XlJQUREdH4+zldLSI/xiHPxwOd3d3pWn4559/xrx587Br1y4kJyfD1dUVOp0Ow4fbyn344Ye47777EB0dzT5ImbsOkQRJKgKRDFF0qXReHIapDiQRTGdyoG3CJpard9QNnFF8OLPeBR+luQh8fHwA2Ea+pKen47XXXkN+UREC3N1hUanQrVs3REdHo0WLFkqLxL59+7B3714AAM/xEFUirFYrTCYTeEHAv8fPwnvgG3BzcUZYWJjSoRUA7rvvPuVnPz8/LF68GFqtFnv37kVycnLtXQCGqYM4ToAoOju6GsxdgiQZHF+3HnTUrdrUYbJZsnU4vQPEx8fj2WefRUuDAfsSZiI1NVVJu753714MGjQIADBp0iRsW78R8/wD4Onmjnbt2qFt27YwmUx45K0kGP2CkLr0Rfw2oStMJhMaNGgAwJbfICwsDM8//zy0Wi2ICF27dsW4cePwzTffQKvVOvL0GYZh7i4yAWLdal1jLR8VkPLNMF/MB3gOyq9L5KFrVv9yVVSUXh0A0tLS4MFxSJ89G7vO/QnwPMAL4AQe0xb9AgBQp/yDzN+voJuzM75qHoq/N/2B4OhwzP3oK2Sb3PD4s2/htcAi5BcXw9fDEyPeexdNfXyQ+OKL8PPwxLTFXyDYxwcFW7ci+coVXLlyBa1bt1bqIEkS/vjjD8yfPx8mk4kNG2QYhqkBZJXBCXWrrYEFH1eRTDCdygFJBMFZDW24Ozi+bkWKt6JsevV+/foBsOXf2LRpEwZpbY+QjBv2gJcBngicDMjpufAQBRz7dTsG+PqiUAMUep0EyTIKG2ViYdFOmEoeQpe9a5F73Ja2/YgkYePpU3jJyxs0422cI8KKM6fR09kFF54dg5jp03HgwAG7uo0YMQJNmzbFpEmTWODBMAxTUySqc4MlWPABwJJaCGtGMTShRvCaO++STJgwQelkGhMTgzlz5qCwsBC/vx2M6C7jsXHWRgQEBCAhIQEAMPiNN/Duu+/ix7wCtJ08Cm5ubrh4dT6YJm090UebhfW7PsBRDw9ofv4JJ06exP+9+CJ8GzfGwKTvkZZ+BdPfeQeiqQRvb9iAjEf6wEmtQoNr8hIYDAaWr4BhGKaGkUQACz7qFinfDKnQAl0LT0dXpcaUdjKdOnUqUlNTER0djTVr1mD0sdEwqAw4f/68Mp8EAEyZMgUcx2H+/PmYOHEiiAje3t748ccfMfXUBGihxeXUVOxKTsbPq1bB3d0d7du3x+HDh9G6Ywc4OTnh4YcfxtfffQcPNzdkAOBYywbDMIxDkMQeu9QpcpEFprO50Le882eJjI+PR3x8vPK6xFoCHAPUghpbtmyxKyuKIqZNm4Zp06aV28+kcwSdrMXhw4dv6rhSgW0unIqCj2uPyzAMw9QAicCpWctHnSAVWmA+k3tHt3hcT6HFFhRsOr8JPnofCLwAgRMg8iIEToDACxA50W49Bw5mERDOZ0DKzQUEwTZ8SxBswcXVybTsSFdnAuZZywfDMIwjsMcudYjpZDb0Ud6OrobDFFgKANiCj03nN1XpvULyQRyPbV/xRo6zD0quBiOcWnVb9WUY5s6zYMECTJw4EUVFRcq6Ro0a4dFHH8Xy5cuRkpKiPBKOjo5G+/bt8fnnn9uV12q1aNu2LS5fvoyzZ89WONOvKNpyFJUVHh6Oo0eP1tCZ1ZwFCxbgvffeQ2pqKqKiopCYmKjM23Uti8WChIQELFm0GJfSLiM8PByzZs1Cz549Kyw/c+ZMTJ48GePGjavx5I93bYbT4oMZd22rBwBIsoQL+RcAAAIvQJIlSCTBKlshkVThaytZYTlxElEFHlCrtIAsgSRZ+ZckKyDJIFkCyqznRBHGRweANxgcfNYMw9QVI0eOxOLFi2+qLM/zcHd3R0ZGxm0dk+d5iKLtO7e/vz9Gjhyp9HFztEGDBmHFihWQJAkGgwGJiYkYMWKEXZmkpCQMGzYMc+fOxeLFi5GcnAwigkajwZQpUzBlyhSl7JAhQ7B8+XIlGNPr9XjggQewceNG/P3332jVqpXdvpOTkzFo0CC4uLjg/vvvv6Xgo0r37xqcY+aW1PTEcpLJSoX/ppMls7hG9s8wDMNUbv78+eTk5FTx5HoOWO655x5HXxJ64YUXCACNGDGCfv75Z2ratClxHEcHDx60KxcTE0Njx46lmJgY4nmepk2bRh4eHhQZGUkA6Ntvv1XKTpkyhZycnGjs2LG06ovl1LFDRwJA7du3p7i4OLv95ufnU2hoKG3YsIG6dOlyyxMXVuX+fdcFH0WHMurlzLQMwzD13bJly4jn+ZsODIxGY40EHHq9nvr27UsAqFu3bo6+LGQwGKhly5bKa4vFQjzPU48ePYjIFrAFBgYSAAoNDSWe52ngwIFERDRs2DDq06cP+fv7U3BwMJnNZnrzzTepcePGBIAaNGhAP3/2PcmyTBzHUaNGjcjX15d69+5Nfn5+BIDuu+8+evHFF4mIai34qFtjb2oDz7Gk8gzDMA7w2muvQZZvfpqKvLy8GqmHLMv45ZdfwPM8hg8fXiPHuJEFCxYgODgYarUahYWFdo9BRFFEcHAw/vnnHyQlJWHChAlo1qwZAODkyZOQZVnJWu3j44PU1FSo1WpcuHABU6ZMwSeffILExEQ88sgjkCQJjz73BIYMGQIiQkpKCjIyMhAVFYUFCxYAAE6fPq3keaotd91tWC621onnewzDMHcTs9mMU6dOVek9VQlUqqKkpASyLKNp06YYOnRojRzjekoDimnTpuHbb78FACxfvhxXrlxRynh4eCA/Px+zZ89G8+bNsX//fuW9HMfhjz/+wEcffQRZlnHp0iWls+1XX32FV199FQ8//DD69++Py5cvw2q1IikpCR4eHnj66achiiJmzJiBtm3bAgDGjx9f63Nu3VXBhzWjGCofvaOrwTAMc9e5dOmSo6ugaNSoEQDg1KlTWLp0aa0ff/bs2Rg9ejRGjBiBxo0bA7BNhfHFF1+UK7tnzx6cPXsWkydPhiAIUKlUeOSRR8DzPJ5//nl88MEHSElJUTJFm0wmJZAYOHAgNm7ciHZRbaBSqZCVlYXLly8rx9yzZw8A4KWXXoIoihBFEVu3bsW8efMgimKFI4eqy10VfPAuashFFkdXg2EY5q6TlZVV5fdwHFetLdWlw3azsrLAcRy6du1a648bzGYz9uzZg27dugEAwsLCAAANGjTA9u3blXKZmZnQ6/WQJAlWqxVOTk7KPF3h4eFwc3NDgwYN4OXlhRkzZkCv10Oj0aBHjx6YPXs2Dh09BL1eD6tkxcFjh8FxHIxGI1avXo2+ffsCALp27QrAFgzt378f+/fvR9u2bREXF4f9+/fX6Jxbd1WeD47jbMlWGIZhmFrl7l71WcGpmjNBBAYG4uzZs8jNzYVWq0WrVq1w4sSJaj3GjWRkZECSJPj4+AAAnJycYDAYkJaWBsPVdARWqxVnz55F586dsWXLFvj7++O5556DLMtITk5Gs2bNkJmZCZ7n4eLigiFDhmDatGkwGo3w8PCALMto0ezqnFk84NPEC5lnspGfnw8A6NSpEx555BGl5SM1NVVpOamtObfuqpYPCNUbRTMMwzA3x9/fX/nZUZ/DZ8+eVX6eOXMmPvnkE/Tv398hdSlr1KhRyMjIwOnTp7F69Wq0bNkSRIQPPvgAPM/j2LFjUKlUINsIVWV6C1mW0efBgWjdujWIAL+GQVizfhMys3Ng8HOCc1tn8DoeacfTYbVYYbVa8fLLL4PnebsOpw5xS+NpalCND7U9mFEj+2UYhmGuLyQkxOF5PQAQx3EUEBBA8fHxZDKZavUamEwmEgSBVq5cabc+KCiIOI4jAGQwGOjzzz8nItswXJ7nKSQkhIqLi+mNJ7655nw4El19yHf4HAqatJoEJ3dyf3AMiW7+BO6/Yc0cz1FCQkK5+gCgV155pVrOjQ21vQ7BRQ0pz+ToajAMw9x13n77bbsZtB2Frg45zc/Ph1qtrtVjq9Vqpe9GKVmWYbVa8c4774CIUFBQgFGjRsFsNqOoqAiCIOD111/HmTNnkGLYArVKhEYQ0T16CIwR90Pf7F5ofJvgpQfDoIUFPfyt+Gr5T3jgpQXQBrWEoNLC3csPr7zyCgCgoKBA6eMBAGlpadi/fz/Onz9fexeiWsKdalTTLR9EREUH0mts3wzDMEzlEhMTyc3NTWmBiIiIoB07dlBiYiJpNBoCQJ6enrRt7RZ675FnyU2vU769qziO7vf0oed6PU2+xkBSqzSkc3auUqvH4sWLHX0JaNmyZaTRaGjJkiV0+PBheuaZZ8hoNFJqair9mZVHzfsOoLhxE+jixYsEgIYMGUKenp6kVqupWbNm5OPjQxqNhrKzs6lLly4U070/BU1aTUGTVlOr9veSWq0mtVpNHh4e1Pm++4kX1CSq1Mrxf//99wqvzfDhw2/rvGotw2lCQgIBsMuGVlxcTM8//zy5u7uTwWCgAQMGUGpq6k3vszaCD3N6EZku5tfY/hmGYZjbI0kyffncJlo+djN9+/xmmv/sJrqQlk9yYSZtmr+Jls3YQRn1+HM8MTGRAgMDSa1WU0xMDO3YsYOIiHw27yNVVBvS9niEdp06QwBo0KBBpFKpCACJokiNGjWi6OhoZV/p6Zvoq422xy4Bzy8lvZe/ElDwokh+ITGk0miU8gsXLqSWLVuS89XALSwsjH777bfbPqeq3L9veWK5yiahee655/Drr79iyZIlcHV1RXx8PHiex19//XVT+62NieWICCVHsqCL8KiR/TMMwzC3Lz+rBP9svgAXDx0aRXnC2b12E2E5wv68Irx24iJau+gxuaEXnPQ6CIKATz/9FLGxsZgzZw6WLl2K+++/H2vXrgUA7N4zGAUFRyELQRj1uhmpe3egef8hEJ1ckJuSgmOrvoOfvzdSLlwGAPzyyy8QBAGhoaEICwvDo48+ilWrVmHfvn1o3rz5Lde9xieWq2wSmpycHFKpVLR8+XKl7JEjRwgAbd++/ab2XRstH9Y8ExXuS6ux/TMMwzBMdbjRvC9ERHv3Dad//n2eiIj8/Pxo/vz5yraCglTSagQKDw+qcP8AaOXKleTm5qZ0cr1VNd7hdOzYsejVq5eSJKXUnj17YLFY7NY3bdoUgYGBdslTHE1wVkPl74SS49mOrgrDMAzDVMhsNqO4uBhHjhzB0qVLceTIEYwdO1ZJ/nX+wmI89JAv3nvvV8hSEQCgsLAQhw4dwunTp/Hnn3+id+/HwAEoKChW9ntth9MVK1agoKAAQUFBtXZuVU4ytmzZMuzduxfJycnltpVObmM0Gu3Wl058UxGTyQST6b/RJzU1kdC1VN568FoRxUcyoWvGHr8wDMMwdUtGRgZkWcaLL76IqVOnIjU1FdHR0Rg0aBBOnDiBEydm4NLlXOh0zREY9AwAoF27dli0aBE+//xzODs7IyqqGSSZkJ7+35ft3bt34/7771def/XVVwCAr7/+ulyjQk2pUsvHhQsXMG7cOHzzzTfVNglNQkICXF1dlaVhw4bVst+bIbioofIzoOhABshaMxMYMUxdUzqbplarRWxsLHbt2lVpWYvFgunTpyMkJARarRZRUVHKc+aKzJw5ExzH4cUXX6yBmjNM/XOrf28qlUppiVizZg2WL18Ok8mEp556CuvWrcPu3bvR55GzsFiA0aPfwpdLdyI8PBzbtm0Dz/OwWq3Izc3FxYuX0Pv+QPA8j9dffx2NGjXCQw89hEaNGmHcuHFITk7GK6+8Ak9PT0ycOLG2LkvV+nysXLmSAJAgCMqCq8OlBEGgjRs3EgDKzs62e19gYCDNnj27wn2WlJRQbm6usly4cKHG+3xcS7bKVLg/jaRCc60dk2EcYdmyZcTzvN3wOp7nac2aNRWWHz9+PKnVaiX5UemSmJiolOnTpw+Jomi33dPTk44ePVpbp8UwddKyZctIrVbTF198QYcOHaLRo0eT0WiktDRbn8P58+dTUFAQaTQaiomJoSeffJL8/f1p0qRJpFKp6IknniAAFBsbS66urjRx4kTy9fUljuPIycmJ3hzShka18yOB50klCtS7Q0tqGuhDWrXt79Hfw5XWTo+jYfc2IU9PN/Lw8KDVq1fTmTNnaPny5eTk5ERz584lIqKuXbvSM888c1vnW2NDbfPy8ujAgQN2S9u2bWno0KF04MABpcPpDz/8oLzn6NGjda7DaUVkWaaiI5lUcjaXZFmu1WMzzO249gNs586ddtsHDhyofFG4dikNRDQaDaWlpVFhYSGFhYVVWraybQCUD0u1Wk0AyNfXlwoKChx0VRjG8WJiYmjs2LHKa0mSyN/fnxISEioMTDjOloW07Pvc3NwoLCyMnJycyMXFhX755Rfy9fWlvn37kobj6IegYFJzHDVSq+kevYHe9vWln4Mb0SPOzuTC8+QrCNRQa6BGAX40cuRIu/oNGDCA4uLiiIjo/vvvrz95PojIbrQLEdGYMWMoMDCQNm/eTLt376YOHTpQhw4dbnp/jgo+SlnzTFR0IJ0s6UUOOT7DVMWNvlm98MILBIB8fHzsAoVrWypKP/SubeG43qLX6ytcXzbQad68eYVlAgIC6Ndff3Xw1WOYmlNZGvVhw4ZRnz59KgxMOI6jfv362b2vU6dOSnAfGhpql5DsobAwchdFW0uIwUB/rF9Ff2xYTXM/mEmNgoPpiccHEgDyUmtp0vDhFBQURMeOHaNXXnmFFi1aRB4eHpSQkECvvPIKcRxH69evv61zdmjwUZpkzM3NjfR6PfXv358uX7580/tzdPBBRCSZrCwLKlMvVPbNqk+fPhQUFFSlzI+1vQiCQAcPHnTg1WOYmpOSkkIA6O+//7Zb//LLL1Pbtm0rDEyCg4PJYDAQANq2bRutX7+edDqdXUAfExNDX3/9NRkMBuKuruvatSvNnTuXVCqVUlYQBCWT7JIW91LeX3/TpEmTiOM45UuGIAjk5eVFXbt2ve3Ag6iWg4/q5sjgQzZbqehQBhUfyyJZYo9emLqtsm9WnTt3Jo7jaOTIkUqrhqMDjRstQ4cOdcxFZJgacr3gIzo6usJtY8eOJVdXVyUw8Pb2JicnJwJAWq2WNBoNHT9+nIqLi2nx4sWkEUXiAXIWRTKqVNQrIIAaGAykUqmI53kyGo3UvnVrOnbvAFoyYwYFBARQz549ydfXl1QqFYmiSFOnTq22c2YTy92i4iNZ0Ia7QxvmBo53zJTPDHOzMjIyIEkSfHx87NYfP34cXl5e2LlzJwCAbi2Jca0oHd329ddfY8mSJY6tDMNUI09PTwiCgLS0NAD/jXr54IMPcPr0aQBA1ooTSJu3V1noSD4auQaA53g09wvDlStXUFhQCJWggrOoh8lkQnh4OAx6PcaNfR4iz0EGkG+1olCSsO7SJbzg4oLfGjZEE5UKOTk58DtlO9arc+fC29sb58+fR1JSEg4fPox7770XM2bMQEpKSq1fHxZ8lCUTwGIOph4zm81IS0uDi4sLDh065OjqXNf48eOxZ88e5fVHH33kwNowTPUqO3ttUlISJkyYgNdffx1eXl4IDQ0FABw/fBQqXwPUgS5QB7ogS86Hn48fvIweOJhyFA+27oIALz/c0zIG6QVZUKlU6NKlC759/x28/PRTaOztAQ8nPVSCAAJgJYKqoS8+LCnEJUkCD+CkVo1zHq4oMpuwf/9+vPvuu+jcuTOaNGmCBx98ECqVyiF/e1VOMnYn0zZzR8nxbOiauju6KjXux+M/4nj2cRi1Rhg1RmiF//K2cBwH7moUVvbnctvA2W/nrq675r1lt4ucCIEXIPIiBO6/fwVesG3jBKgEFRo6NwTPsdj4eq79ZgXYWkPI9jjVgTW7OZ988gnuu+8+5XXXrl0dVxmGqQETJkzA8OHD8euvv+LRRx/Frl27YDKZ8MsvvyAoMAgzfl+I1KZWzPrgXciyjE3PbEP37t1RdHQXZCIcuXIK0PAIjGoC4cAO6HQ6/Pvvv/hCrUZQUBCySUDD4EbYf/AQVKIIyDIWZuQivbAYWmdncFYr+gx/ClfSinDfvffip9W/Yv/+/WjevDn27duH2bNnw9PTE9u2bav1a3PLE8vVlNqYWO56LFeKYM0qAcdzUAc6g9femfFZ1++74krxFXjqPJFjyoFVtjq6SnYeavQQ3u38rqOrUefFxsYiJiYGiYmJAICLFy+iYcOG8PDwQGZmpoNrd/PUarVdpmOGuVPMmTMH48ePhyiKaN26NebNm4fY2Fjc07Yj/tqzHZ3ad8RnX3yOOXPm4Ntvv4Wfnx9OnDgBABAEATzPIzwkDNn5OUhLS4NKFGGVJFgsFvA8j3vuuQcTJ07E4sWL8eOPP9ode/DgwZg68WXsnP05Oo4fhft6P4Ls7GxwHAd/f3+0aNECv/zyC0JDQ3Hs2LHbPteq3L/vzDvrbVB566Hy1oOsMswX8yGXSAAA0U0D0VsPjrsznsvoVDqMaDwCE9pOsH1TBv33L67GowS716XbS3+2FbHfVm57mXIEgiRLkEiCVbZCIgmSLMFKVkiyhJM5J/HqtlcBAK5q19q5EPVc6Tertm3bIiYmBh988AEAIDs7GwCgVQkosUiOrOJNMZvNWLVqFfr06ePoqjBMtRo0aBDGjx+PP/74Ax06dFDWx0S2wdkTp3Eh5SKio6MRHR2NjRs3IjY2Fv3798dPP/2ERo0aobCgEIePH4Es27JwW61WeHh44OGHH8bw4cPRt29f9O3bt8Ks40lJSUhKSsIznbqiu5MBa9euRa9evZCSkoLTp08jLS0NPXr0wNmzZ2vrcihY8FEJTuShCf7vBmjNKkHJoUyofA0QPXUOrFn1EDgBVrK1diiPThwUV1llK+bvm48vD3+JYJdgzLhnBqK8ohxTmXpm8ODBSE9Pt5v3ITQ0VPnmxAsCUIeDD47jsGXLFvTr1w+TJk1iwQdzxyntSH3ffffBz88PJpMJ2dnZUPEcikssEIt5RDQKwmuD+sHz0mlMeGI2kv+yPQY5efKksh+e55UAxElN8JIuYsKY0SgsLATPcygsLLSV4zho1Wr4uBtxOTMLZosV94Q0hdlswjvv2KYzWbRoEZydnbF+/Xq88847uPfee2v3ogBgQ22rqHBvmqOrUC36/9yf3tnxjqOrQbIs05t/v0lRS6No4b6FVGgudHSV6r2FCxcqQ1i5Kg55re2lNLeA0WikkJAQB185hqkepVmHxasJwDiOo6eeeop4nie9Xk8vvfQ4ASCe42nZ43OppW8ocRxHPMeTyAs04d7hJHA8cRxHIm8bcqv8TXMceThriedAeo2a3J2dqF1oY2VIPQfQiAfvo4jABiQKAnEAffHMy/Tv3j0kCAKtXr1aqWdWVhbxPE8PPfRQtZx3Ve7frOWjCiRZwv78A7h8PKdcp0ye4yvsaFm2VeHadRWV25O2B+5adzQ2Nr5uXegGXXVWLl2JZZ8sQ1Z6Fpo0a4IXpr+AZtHNlO0nsk+gtXdrALbJjBISErB06VKkpKQgPDwcs2bNQs+ePZXyCQkJWLFiBY4ePQqdToeOHTti1qxZCA8Pv6VrWWp/+n4sP74c41qPw9Mtn76tfTE2o0aNQnx8PGRZxvX/lziWKIr466+/MG7cOOTk5OD//u//HF0lhrltpSNbPv74Y3z44YeQJAnHjh3D8uXLIYoiioqK8MEHywAAMsl4evVr0Gq1cHNzg8lkQu/evbHw5yRIdPUxC0m4cuWKsn+e59G4mT+Sd51GsdmCIpMZWfkFynYCsDPlCgYMewozZsxAYGAgrN4NwKs1kCQJ//77LyIiInDy5Em8/PLL0Ov1SqtJbWIdTqvgywNf4o+ta7HT+YCjq3JduTtzcfGzi/Af7g9dYx0y12ciNzkXYTPDILr8F28+G/ks4lvFY9KkSfj666/x2WefoWnTpli3bh0mTJiAv//+G61atQIA9OzZE48//jjatWsHq9WKV199FQcPHsThw4dhMBhuqZ5Hs47i2Q3PwlXjim8e/gbOaudqOX/G1hF17969CA8Pr/NDbkuNGjUKn3/+uaOrwTC3JTY2FlqtFufOncO5c+cQGhqKCxcuoKSkBBzHwdnZGXl5eeXex3EciAgNGjRAUVERsrKy7B61VITjOBiNRuTl5UGSKn68umDBAqguW/HgqD548MEHcebMGaWsq6sr8vLyHNLhlAUfVfDqzy/jSMYRfPz4Injpvew7WZbpnEllOnACtvUyyfbryryXynTkzCzOhFpQw0nlZHfsqnR07dG5B6LbRGPWh7MAALIsIyo0Ck8/9zTG/W+cUs5D66H0en7ttdcwduxYZdujjz4KnU6Hr7/+usJjpKenw9vbG1u3bkXnzp1vum6A7dy/P/Y93t/9PhobG+Pjbh/DTetWpX0w15eUlIS4uDhIkgSNRmM3kkQQhEo/qByhqKgIOl3970fFMGazGVqtFoIg4N1338WECROg0+lQXFwMANcNJkRRhNVqvWHAUVVqtRqzX5yBh8c8hvj4eGzZsgVFRUXgeR6+vr5IT09HYGCgXf+SW1WV+zdLpFAF97Z8AN5WD7y2ZAJe+3USfr/wO4gIKl4FlaCCWlBDI2igFbXQiTroVXroVXoYVAY4q53honaBq8YVrhpXGLVGuGnd4K51h4fOA546T3jqPBHuHo5Gro3gpfeyW0q332hxEVzwz75/8EjPR5R13gZvdH+wO/7d/a9d2dKAxmQylesprdPprjv2Ozc3FwDg7l61nChmyYyn1z+NGTtnoE9IHyzusZgFHjVg8ODBmDNnDvR6/XWHsAYFBYHnb/5jIKKFM/Q6TaXbn3nmGfz777/K67lz52L58uXw8/ODSqUCAIwZMwY8z8NgMODDDz9kgQdzxyjNs1N29EnZx4mVBRUcx8FqtQ0A8PDwqPJxGwV4QRTK/x03a9wQZrMZGZcPo7ioCOvWrcP333+PgoICXLx4ESkpKXBycqpgj7WgWnqZVKO63uE0z5RH3x/7niYkxdPIxMfp+U9G0Hvb36VjWcccXTUiuv58AjExMRW+Z8iQIRQREUHHjx8nSZKUyYzUanWF5SVJol69elGnTp2qXL+VJ1ZSiyUt6M+Lf1b5vcytS0xMVCaZ4jiOIiIiaMeOHURkmxxSo1bdsHOou7s7JUydQSr++mWvN5dM69atiYhIEATy9PR05CVhmGp35swZAkAJCQnUtm1b4jiOFi1adMO/rbITxxkMBmVyuWu3VWVx14K8Dba/xZ1Pt6Wz25YTANq4caNS36ysLBIEgcLCwqrl/NncLjXIWe2MgWED8cGgREyOewshkc1x5sARzPpmGl5cMRarTq1Cdkm2o6tZJXPnzkVoaCiaNm0KtVqN+Ph4jBgxotJvxGPHjsXBgwexbNmyKh/Lz+AHANhwbkOdS2x2J4uPj0dWVhaICLIs49ChQ4iNjQUAbNmyBSUms5IZlYjgEhCivJfnebz66qvIzMzEpDdehUQSDCodLkz6AyeTjmBEvyF2xzIYbPkEyu6vdCmbTp1h6qvSeVq0Wi1iY2Oxa9cuu+2SJGHfvn1o0qQJPv300xvur+xj0MLCQrsOoDfziLRFs6bwdLdvQc4qATKLOXi4uSLS1wlB3q5o1qwZxo8fjx07dmDt2rWIjo6GJEmOyYhcLeFONarrLR8VMUtmWndmHU1IiqcRiY/TiPmP0/9WjKNN5zaRLNfu7LiVzXQ6bNgw6tOnz3XfW1xcTBcvXiRZlmnixIkUERFRrszYsWOpQYMGdPr06Vuu408nfqLopdH02KrH6Hzu+VveD1NzJEmmY6l5ZLFKNywryzKZC0tqoVYM43jLli0jtVpNX3zxBR06dIhGjx5NRqOR0tLSlJbnXr16EQAaOHBgrQxZNxgMZDQaK2yBdDIYSCNwFBneiMaMGUNarVYp4+3tTYMGDaKmTZtWy7Wpyv2bBR/VLK0wjVYcX0ETfvg/enbeUPrfTy/S5nObSZJv/CFeXWJiYig+Pl55LUkSBQQEUEJCwk2932w2U0hICE2ePFlZJ8syjR07lvz9/en48eO3Xcd/rvxDvVb0ok7fdaIdl3bc9v4YhqmfSnNiaDQaiomJof/973+Vvm7Xrh2NHj2aGjduTBqNhlq2bElDhw6t9LWvry8BoHHjxhERUUJCwnVf34yYmBgaO3as8lqSJPL396eEhAQymUzE8zyJokgAKCQkhHier5UApLJFEAQ6+HwMLZz6HGm1Wtq7dy8VFBTQpUuXiIho0KBB9PDDD1fL75IFH3XEpnObaNy3z9Ez84bSy6sn0JHMI7Vy3GXLlpFGo6ElS5bQ4cOH6ZlnniGj0UipqalERPTkk0/SK6+8opTfsWMH/fjjj3Tq1Cn6448/6IEHHqBGjRpRdna2Uua5554jV1dX2rJlC12+fFlZioqKbrmeOSU59PS6pylqaRSdyDpxy/thGKZ+urYV4YEHHiAApFKV71dUekMHQNOnT6dTp05R165dy20rXcre9ENDQ8nLy6vCmzPHceTr60u//fbbDet7My3LMTExdM8999jtv2xrg91SQf8orQhS2yapJU+NgVSVBC88j6vXquKgQ6P+b/vfX/Wm3P3zacCAARQXF6fUOysri1xdXemTTz6plt8nCz7qmK0XttLoL4bRqMQhNH7RGJry6yv00b6PaOuFrZRelF4jx0xMTKTAwEBSq9UUExOjdC4ksnUwHD58uPJ6y5Yt1KxZM9JoNOTh4UFPPvkkpaSk2O2vsqh68eLFt1VPs9VMnb7rRNP+mnZb+2EYpv65thXB09Oz0s+a0kyhoiiSVqulixcvVhh0VBaAXG+/LVq0IJVKRQcPHrxufW+mQ3/pl7+GDRsSAAoICCCe5+2ylF67qFUVBSeVd9z2cFPfVKsHz4O6dWxAv3/Vi1Iv/kD3338/eXt70+nTp2n9+vUUFRVFsbGxZDabq+X3WZX7N8vzUUusshXbUrZhz6XdyLyYipyMTBRZi8AB8Ajww/8efAW+Bl9HV9Mhvjv6Hd7Z+Q5eiXkFcc3iHF0dhmFqgdlshl6vx8iRI7F+/XpcvHjxpjpXuri4ID8/HwBu2FFSrVbDbDbfcJ9t27bFqVOn8N5772HUqFF2267NAG0ymTB79myMHz9eKXPfA93w119/QaUSwQFwdnVDZnoarBbbsTVaHUwlxTesR00Z/HBj9B8+HE8OnQGLxQK1Wg13d3c8+uijePvtt+Hq6lotx6nS/btawp1qdCe2fFRElmW6mH+RVp1cRc9/PpImrprg6Co51Hu73qOWS1rSxrMbb1yYYZh6r7QVQRRF+uKLLyg8PPym+zEYDAZSq8t/+6/08cbVVpC+fftWuE0QBFKpVHTo0KFy9Zw4cSL5+/vTc889R/7+/kpryZdffqmUiY69h9R+4eQ/+hPyH/0JaZvEVviIRR9xP4G/fmuN3SLeeAj8zS4BAV70/PPPk1arrbHfKRtqWw9wHIcApwA8EvIIunXujcxzl3Ek84ijq+UwE9pOQPfg7pj05yQcy7r9NL8Mw9QPffv2RVxc3E2n9xZFEYWFhRW2aJSUlFT6PlmW8dtvv1W4TZIkPPHEE4iIiCi37auvvkKPHj2waNEizJgxAy1btoSTkxOefvppXLlyBbIsI+3CGejD2mPmiO74d/ZwuBacAwB4e3ujbdt2tmSMRHDOPAwvDzcIggCV0Q/ej01D5NMfQNS7gONFABw8W/WA2uhztdIE8ALEJuEAL8DtjVkwvPCK3QzkGg2Hae8EYtXGCPTq6w6OAx5/0gurNrXAz5ta4Mc1zRAT7YsmbaPg5OSExo2vP29YbWETy9UB3YO7Y4Pnb5j33Ux4NmsAXw9/eGo94an/Lxupt94bKl7l6KrWGJ7jMaPTDDzx2xN4a8db+PrhitO6MwxzZyhtlg8NDUVGRsZNv0+r1cLb2xtZWVkoKChQMoPeDIvFUum2pUuX4qWXXkLLli3t1ptMJmzZsgWjR4/GiBEjoNfrMWSILbfNzJkzUVhYiOKiQji17AaNSkD3Lh2RlpoKwBbU7N6djAceeAD79u1DRkYGJEmCm5sb8vIzkP13Ehr46mEt+m+ul7xDv8PT0xOXcgCQBBBBvJIKiWTkz3gNVpUKoP+mSWjWLArvTDuEPn36YNuWFDg7u6Bd9CtoF/EEAEDv7IJxTo+iZM9BXDx4BoMGDbrp61WTWMtHHWBQGfDhwPlo17kLzGkFOLH7X6zf/DO+/OUTfPj9O3ht6QQ8t3gEtl/a7uiq1iiNoIG3zhv/pP+DjOKb/zBiGKb+KZ1crbI5RTiOq7AvQmFhIbRaLWJiYipsqagqQRBgNBphMBgwf/78ctu7deuGM2fOICIiArIsw93dHaIogogwZ84c7N+/H2vXroVozkdcxybYu3cvAKB79+7geR48z2Pr1q3Izs5W5loaM2YMHhzxP1guH8fevXshiqKS1NFsNuPSpUu2g1/t02IVDfDy8rIFWlfniSntH7N//35YLBb8+OOPyM3NRV5eHl566SX4+fnBz88P8c+NwcW/1yPj4kWcPn0aGzduRHJy8m1ft9vFOpzWUTLJyDHlIKM4A+lF6Vi59wcUnctCl64PY3CzwY6uXo1ITk3GyHUj0b9Jf7zZ8c0qTabHMEz9cunSJQQEBECtVmPhwoUYPXq0XQdStVoNq9V605OsNfVqjKPppyvcJvAC+vbri+7du2PMmDHltru7u8NisWDAgAFYsmSJ3bYDBw4gMjISHMeB53mEhISgW7du+PjjjyGKIjiOQ1RUFHKjhiB/0ydoHdEEq1evBsdx4DgOWq0WHMfZZS3lOA68IECSZAg8DyIZPM9ftxVHrdHAzd0daVlZQAXzNXEcpwQx3t7eSElJKXPtbHX5888/sGHDBnz44Yc4fPgwAgICbnxhq4BNLHcH4Dke7lp3hLmFoVNAJ8zq9T4atYrA1o2/4X8rxyE51fGRa3WiqzPd6kQdJrSZwAIPhrnDeXp6QhAEDB8+HNOnTy+33Ww233A6eaHM58SJjHOVlpVkCStWrMDq1asr3G6xWJCfn4+4uPKj7Uonetu8eTPOnTuHo0eP4sKFC5BlGQEBAdi7dy+ioqJw8qspuHz2BIYNGwZBEKDX6yHLMoqKilBSUmI3XYXRaLR9xnEcBFHE2rVr8b///c/uuG5ubnafg0cOH8b4Sa8AVwOUsvvjOA4rV65EcnIy/P39ceXKFVy5cgUnTpyAIAjwi70f/qGh6NSpE9544w00adIEH330UaXXqzaw4KOeEHgBL3eahEH9RqDYVIRPV82DTNU37bIjEREW/rMQa8+uxfRO02HUGh1dJYZhapharUabNm2g0Whw7tw5fPfdd1WaYRkcBw/xv26LElU8TJfjAJVo229FwQfHcTCbzYiLi8Nff/2FZcuWYf369Vi3bh3WrVuHPXv2gOd5bNq0Cf/88w9WrVqFtWvXwsnJCWl+DfFAmhn6F18FtBqQLGHauUJoQprCpLbNaqvy8YdEAAkCeJ6DyAM6KQ9dm2jh7wRIlhL8MG0QRgvf29UrOzsbRKT0LY1o0QKvvjQBIAKvUqHXk8PgHdAAHM+DiPDdpt/x95VMlMgEk8mEj9dtRHKBCZIkIfvYP2jdvaey7xvNWl4bWPBRz9zX8D48dd8zEE0cPtjxPnJNuY6u0m2RZAlvbH8DH//zMeKj49EzuOeN38QwzB1hwoQJ+Oyzz7B06VJERkaiffv2FZYrbQDgOQ7C1QCFEwRkVJIXRBR5eHqq0bWrE4gAi7X8FzVBEAAADz30EHQ6ndLykJCQgPfeew/Hjx/HiRMnsHXrVnh4eGD9+vXYuHEjJk6cCIvFAlmWwUdEAQB+eS8BukDbKJLs1Avg3D1hzc601VOnB2QJZLFAJoKHDsgsIhzPFmDmtPBwdcKn23PQ5O3TV+tlOz+VyEMjAPzVevr5+ODee+6BRqWCbLHgzJ7duJJyEXqdDgCQlDgXz3fvCt3V9x/57Resn/s+NBoNrPm56NSxAyRJwtdff43t27fj8uXLN/trqhk1NuD3Ft0teT5uhyzL9Mmej+nZhU/Scx8Ppw93zqYzOWccXa1b8vm/n1Pk0khadXKVo6vCMIwDVJaNOTExkTQaDfEcT0HeTWn739uVbMwcx5GgUlGryAh6//2eNGN2YwoMVJEgCsTrXMjQ/H76bU0vysraTl26dKFx48bRyJEjKSgoiNRqNTk5OZFWqyWVSqUcs6CggKZNm0bt2rUrlwE6ICBAye9RmjVVr9dTl29/ont/+4NCQkKUlPAuLi7UunVrCg4OrjDfhk4ECTxPHAcSBYFGPtyVjE76G+bp0OsrLyOKIml1OhIEQclpolaryWg00n3dulHjgGAln0m7du0oLi6u2iaTK4tlOL1LZBRnYOk/S3Dq30Mwm00wunsgODwc9zS8B2FuYdCr9I6u4nXJJGPgLwMR5BKE2ffNdnR1GIapg376cC9SjuWgcbSXXX6LUr9dyMAv1iLl9aOt3PBUeze0DGpWpeOUlJRg5syZ0Gq1ymgWwPZYeP/+/UhKSoJGo4HJZIIsy1CpVGgz9zNYgkPgNGsKMjIycPbsWYwYMQKZmZlISkpS+qw4OzsrWVkBQAWgoVqN0xXkKuFgiyiuxfMcVCoeLq5qpF8pRtNmbjhzJg+mElvrzyN9GiMvz4ydOy6jpETCV19NRkTzUGRmJsN6Soa6yb2IiHgAfn5+GDx4MAoKCvDrr79W6RrdSFXu3yzPRz3mqfPES+3/B1M7E36/8Du2n9yGI7v3YM+OP8GBg5uzB/zDGyPcKxzBLsFo5NoIBpXB0dVWnM09i+PZx/Fs5LOOrgrDMHVUs47+SDmWA6ul4kcs0e5O2J5jRobZCk8nNd4f1OGWOqxrtVr07t0b+fn5ykiV0v0sWbIE/fr1w4QJE2CxWNC1a1fodDpI+5MhtmyNLVu2YPjw4dBqtfjss8+g0+ng7e2N1NRUqFQquLi4oKCgAEQEXlSjZcMGaC7LuHDuLCQAfqIKKVZbDpLKWgN69vTDQw8H4LVX9wMAThzPUQIkFxcV/tmfiqIiCcOG++Dzzy5h8eJ5ePU1H0iSDka3EDj7ZMDPzw/Z2dlYt24d3n333Spfo+rEWj7uMFbZiuPZx3Es6xgOpvyL9FMXkVeSBw4ADwG5Oh6HzVkQeQFuei148OA4wfbv1Z858ODLrOM522uuTFme48FDsK3n+KvrBPAcD4EXIXD81UUEz/EQedsQMAE8BJ4Hx3GwyCX47fICvB47HYOa9nf0pWMYhimndA6aH374Af369QMAxMbGIjc3F2LDYFinvoeEUH883boleox4Gmq9AV++PhlEBEGlQmj7Dujz6lT88m4Cjvy+CQAQ+OBQ5OzdACetCpcvpYADIBNBz/EoIhndXd1wRJaRXlKEEosFAs+BwEGlUkGSJDz22GP47rvv8MILLyAxMRFarRZEhI8//hgzZtjmbyGSsXfvFiQnH8exbe+g3cN9UVQUhZdffhlarRZ//vknVKrqTVzJWj7uYiIvIsIjAhEeEegf2h+4DygwF+Bc/jkcTD+MpFV70YYa4aKYjdTiXBBHcNUJkCEBsII4M0AyiJNBkAFU8i9nvw5lyqPsdk6GbVqDykfm7DqbikFNa/rKMAzDVF1pVlIfHx9l3YQJExAXFwfPkhJYT51A3LtvoiS/ABtad4Hg7gHO80NQehq0vQbg6OoVOD/rXfx/e/cdHkXxxgH8u7vXk0vvnRQCoYOEXqT3akOaijRBUaT+VFAUEFHpAhZE6SKgKL13QpeS0HsgvV9ydd/fH0eWHAmQQBown+e5B7I3t5nZy+7Nzb7zTva+PdLr447tgClbh6w0PeRyOdYd2IvXW7eFLiMTIGC/PhPZhvs5Pzo0j8Tluxm4e/cudDod+vTpg6tXr+LkyZPgOA56vR4ymQyffPIJqlatij179kAURbi5hSAz8zi+/eUkEr89DBcXN2kxueLueBQVG/l4wdxOzcaKwzdw90Y60u5mgQwWOIW64KVqHmgc6oYAF02J5NggIogkQoQIEgkWIgxbfgJHryXjyP/aQ60Qiv13MgzDPK3cZGgHDx7EiRMnMH36dMTFxUGpVCI7Oxs8z6NajRr4buYsNKhfDzKOQ+0a1fHfmbMF7i838VhOTg44BQe7cC0CR/gj5v0YiDm2X9IUchWMJr11tJjn0atXL5hMJmzevBlpaWmPrLdMJpPSyR9e3RN+DbrDz69PsRyTh2EjH8xD+TlrMLq9NRBLFAkrj9zE4ajb2PDXefxDgJOdAm5hzqhbyR2tIzyhURTPn4g1IZAAAYI0wdto4lHZ25V1PBiGKbdyk6GtWbMGc+bMwYIFC1CvXj1069YN165dw61bt+Dh4SGVN4gi+g4chP8++AAqlQoTJ07EyZMnsXbtWpjNZjRt2hQjPhiBHj17gMyErHMZOPfuOZvf6VDfAVlHs6QAEHutHKGh7hg3zhtnztzFP/9kQybj0alTBCZPbg+TyYL58w9h/fqzSErSwd5eCZVKjlMnB4JLVQEWoMBo3TLEOh8vMJ7n8Gb9QLxZPxAZehOirqbg8KVExJ1PwapT8fhLGYOq9X3Rp1EFeDqoiv33d6rujfHrzuBWSjb8Xcr3zByGYV5MucnQlixZIi0ul5u5VKVW4/VvZqD10PdxNceAc1k5uJ5jRNIPPwIcB0vFCMx+qTXE6s1g/vNPgONw4PZd2J87j4HdGyDVSQOvirUx93/fws7BHhwAvUkPMUuEKIqw8Ca0beOEPXvTceZMLI4fX46hQ++A54GQUDl4/ibuxq3BTz8mY/v2LIwZFoYAZx8MnbAf8fE5OLPpFqo09oZMYwc7u9CyPpQ2WJIxBgDgoJKjdYQnPutaFfPGNsW0MU0QVtsbpw/exqipe/Dh7IOYs/0iztx+eFKzefPmISgoCCqVCvXq1cORI0ceWtZkMuHsv4twZ+FAVPByRo0aNbB58+aSaBrDMMxT+eCDD5CQkACe5xETE4OhQ4dCp9MhrElzHDp0CF8OHYR9309Da1dHTKvgCcvFaPCCAPPZUwhb9D3kH78LnuMAInBpqUgNqotrd2Vw54KRERMPpUIBV0dnKAQ5GtVtCN05HeQya0yGSBbI5So4O3tg5Mgc5OQAnTq9BhfnWnB2fhVZmVOxaZMR3ZuHw8UpEHNW34WDsyNefrk61p+0oFaTRXipy+9wdq5XxkfRFov5YB4pQ2/C+lN3cPJcAlKupYHMIpyruKFvs2DUDnCWyq1atQr9+vWThiRnzpyJ1atX48KFCzZDkrnGjh2LpUuXouXAz3AkVY3evqmYMnE8Dh48iFq1apVmExmGYR4pN+7D09MTqampqFmzJmbPno0flq/E8q3bUcPNCVVDQrB48WKprJ2dHXQ6nRRD5+DggPR065c3Tq6AvUqJ0NBQmEwmRERE4O+//4bZbLbGx+VZ00YuB4gEKJUqm8XpCqLVatGtWzd8/fXXGDNmDPbv34/r16+X2HF5UJE+v4s9xdlTYhlOyy+j2UK/7r1C707aQf3GbqYv1pymTL2JiIgiIyNp2LBhUlmLxUI+Pj40derUAvfl7e1Nc+fOpcRMPYV/upH6/HyYevToQb179y6VtjAMwxRWbGwsAaCDBw/abB/00UjiPb3Jyz+AlEolRUZG0r///ksAaMOGDdS1a1fieZ4EQSA7O7t7WVJ5krt5SplSv/76a0pISKCuXbtKWVQBUFhYmJTBtE3LeqRQKAgAnThxgoiImjVrRi1erkj9XgmkmmGeBIDmzp1LFouFtm7dSmq1mhQKRakep6J8frPbLkyhyQUebzUJxsJPXkarLhVx6dhdvD9lN6b/exrHjh9HgybNpbI8z6NVq1Y4dOhQvv3MmzcP8fHx+PDDD9GmeWOk34hB/WDXAhc7MplMmDRpEkJCQqBSqQq8PTN16lTUrVsXWq0WHh4e6NatGy5cuFAix4BhmBdPbtBpfHy8zfbTUVEQE+Lg89q7+Gj+WvBugXjl9V7geAHLT1xD7Q+nYdymk3hv5U5YBDl4uRzEc3B9fzR6t2gPABg3bhw8PT3xz/r1Nvu+fv06eJ5HhQoK6LLvwngvG2qdOnUgk8mwZ88e7Np9CcvW3sTUYc0BWG8PKRQKDB8+HG+//XbRFuorZeW3Zky5xfMc+jasgG/GNkFQdU8c2R4N0WLBkg23sebYLamcp6cn4uLibF67atUqjBw5EnXr1kVgYCDsXL0R/8cE3Di6A2vXrs232NGnn36KhQsXYs6cOYiOjsaQIUPQvXt3nDx5UiqzZ88eDBs2DIcPH8a2bdtgMpnQpk2bxw5RMgzDFEZu0OmOHTukbaIo4vjRI1CGV0Vsx874w88biR+MhVmlguDihk1H9mFtjg6bzWYc4OXQZ6RBNJmg9vZH1uxvsXzHJqjlcqjlckT4+uOjNk3h5+yImv7eAKxfvHwctUiLF3DipPW6yvOAvT2wYKE3KoYr0bKlHUaOcsXk3/ZJdZrafhQOf7cR9vb2CA4OLv2DVUis88E8MW9HNSb2rIbvRzUBALhUcML6v87jVkr2Q1/z/fffY+DAgfjnn39QtWpVHNj2L8igw3efj0GHnr3y9dSXLFmC//3vf+jQoQOCg4MxdOhQdOjQAd99951UZvPmzXjrrbdQpUoV1KhRA4sXL8bNmzdx/Pjxkmk4wzAvnLwr8MbExGDQoEEwmUxoz3tB+WZnXG/3ErLf7ow29eqiRqAfMjevRZONv2KqLAmuCyYCsKYcyLl9Hca0ZBAHkCAgx2RColGPegOGwdHDF7B3k+JEbqemIy07B7UrVoKjgz0ADpmZBH+7j+FiH4ZAj5dRzX8oatdoJNXTWe6A9KN3sGbNGnTt2rUsDlWhsM4H89Q8PdwhCAI6V9WCRBGL9lmXho6Pj4eXl5dUzmg04vjx42jVqhXc3d3x119/ITs7Gz17vgLHwCq4kS7m66kbDAaoVLbTfAu6PZNXblCXi4tLcTWRYZgX3Ouvv45vv/0WEyZMQM2aNXHixAkAwL/nd2Jc/w9Rp04d2NvbY8eOHRBFEUOHDsWCBQvQtm1b7Ny5E4A18RfHcfBz8ELHNm1RubI151JiYiImTpyI6IsxOH3hHARBgCBY8x8RgAOnY5CZlY1+/fqD53kM/d9sxCakw949GH2HT8KbQz6W6nkx6Tr6/z0WoihizJgxpXuQioB1PpinljskeXDvbvjX9sLd/xIgiiJ27NiBBg0aSOUKSlOsUqkQHFwBGksmzhzYiq5du4KIYMmy3jJp27Ytvv/+e1y8eBGiKGLbtm0F3p7JJYoiPvzwQzRq1AhVq1Yt2YYzDPNCGT58OG7cuAGDwYB///0XANCmUlO82fIVHDlyBOfPn4dMJkNiYiJmzZp1b40VkjKhmkwm+Lp74XpaLDZu24orV65AEAQQEaKjo3Hjxg24urri+PHjmDlzpvR7ne0dcODAAXh4eECr1eLOnTto0aKFVEav10tl50ctg4+3D/bv3w8nJ6dSPDpFVNLRr0XFZrs8m1auXElKpZIGfvotdXn3J3qj79vk5OREcXFxRETUt29fGjZsGAGgjz/+mLy8vEgul1ONGjWoZctWJCg1pHT2ovOffELR4ZWsj8oRtD8klNwFQYr6BkAhAdbI8lwZGRk0YsQICggIIEEQSBAE8vT0JKVSSdWrV6dNmzbZ1HXPnj3UqVMn8vb2JgC0bt260jxUDMOUY3PnzqXAwEBp9kpUVFSB5TIzMwkARQbVJBetkzRTRS6Tk0atIT8ff1IqlOTv608uzi7S9UvgBWoS+BJ5ubrbXNdcXV1tfi7okTsTBgB5eXlJP6tkCmn70i8WkmgRba6LKpWKGjRoQEeOHCnRY8dmuzClLndIcvPvs/Hvr+9h78Gj2Lx5szTKcfPmTaSnp4PjOMyaNQv9+/eHv78/zpw5gx07tgMyFf76agrEP9dI+7Rv3hzzMzORaLHgVX9/zG7RAo01Gly5eRMqADGVKoMsFrz77rvYtm0b6tSpA5VKBaVSiczMTOzcubPAAFWdTocaNWpg3rx5pX2YGIYpx3ID4idOnIgTJ06gRo0aaNu2LRISEvKVzcjIAACcuHkGGbpMjG82BMPr94XJbEJ2TjberdQNG/v+BHujAimpKWgWFAkAEEUL9t04BqUoQpYn43lycjJCXJ3g56gFcD8Zet6k6BwBnZu1BADExcXh/fp9MKnlCAS5+0tlErQ63Lp9S7ouLlmyBGfOnEGbNm3QqlUrxMbGFt8Bexol2g16Amzk49k3fukJev/bvQU+Z2dnR9WqVZN+bvb1NgLHU9MWrejW8OEUHV6JLrVsRRadjoiIPDw8yNfXVyoft2wZcQDZ8zxFh1eirKQkEgSBOnbsSD4+PuTu7k5z586l2rVr0yeffEJE9Mj8IWAjHwzD3PO4fEV5R0Vq1qwpjTY0j2xCYwd+RPYaO2mbjJfbjFo4OTg9dmTj/mt54grYLnC2o8Cft3y/wNf37t2bBEGgf//916Z9ea+LJYGNfDBlqkl1L2QlZmPO9ouwiPcT6BqNRuTk5CAmJkaKGP/vj+8hCDz4a1eQuW07xt29g1/qvgReo4HRaERiYiKSkpKwbt067Nu3D93nzgU4Dh7O1uyqJr0eFosFu3fvxvLly2EymWAwGCAIAvbu3Qvg8QGqDMMweQPic+XNV/TgqEjt2rWlcsdjTmHaTzPg5uEubTOLJpsVwtMy0vL9zurVq9v83DCkLhSCHGZRzF1TDjJegEqmtNbngRXHZ0T9CgD44osvpG3r1q3D/PnzYbFYihysX6pKrAv0hNjIx/NhxsYY6j92Mw2atZ/upuUQ0f0sgSNHjqSAgABSKBTkW7Eahdo5kBwgBc+TvUZDHTt2tCnv4uKSr2fPcRzJAfLz8Sn0t4kRI0ZQTk6OVEez2UwAyN3dnWQyGclkMhIEgapVq5YvToRhmOdb7vXm448/ton56NOnD0VGRhY4KpJ7bZHJZMRxHAkPxKfVCav90OuRUqYgtVxps02r1JJKrirU9Sw3Q2ruIzdmpG3btuTn50ccx5GdnR0tXbqUzGYzLVmyhHiep4oVK5bYMWQjH0yZ+7B9JQwbUhfmZD2++9t2uehXXnlFihifNnE8ruoy4CmX48DufejVuzcOHDiQ7x7roEGDIJPJ0Lp1awCAXBCg5HlM+/xzuLu7w9fXFwAgCALkcrn0OmdnZ2m676JFi9ChQwdp8bugoCAAQGhoKFxcXDB69GioVCpUqlQJ3bt3x5EjRx6bXZVhmOfL7NmzbWI+Vq9eDYPBUOCoSO66VblrstADS6WdvX5e+j8HDgrZ/ZEIg9mIHJPBpnymIRN6kx6FwYNH58avSj8nJycDALZs2YLbt2+jdevW8Pb2Rp8+faBUKjF79mz06pU/l1JZKR+1YJ5LAS4aJDspkHHVmnejoBTFs2fNRICfP/wcfRC1TI8OQgPwJmB012E4NGkTACDMIQi7/tqONpWbQx5H0CjUMFkskMs0mPP3QfjVbQvR3h1Dfz2At+ZsBCdXgRdkUNo5oPfc7fB5qQ0AQJdjwK5duxAbG4uKFStK6Yqjo6MxYcIETJkyBW3btoVCoUC7du3QqVMnTJo0Cbdu3UKFChXQpEkTm+DVvXv3onPnzvDx8QHHcfjrr79K8egyDFOc3NzcAACtWrXC22+/jYiICCxYsAA8z0On0+VLEwAAWVlZ0v85jss3vd9gsiZcVCqVkMllMFlsOxtt2rRB586dn6i+dSMawZhuvYa93r0f5s/5GYC180RE2LJlCy5duoQuXbqga9euOHLkCEwmU7nJeso6H0yxIyIsP3wDo6fthWOqAS07hgLIn6LYaDTi2LFjyMzJRkD1FgCAWApEFZ9qOHv3GgyiHRQyBeIyk3El8TrCPashyLUiso054MAhNLA+LkafwuUT++BaqR5SjBzSSQVjdiZEixkmgx4x/x1DzIHNADiIZiOUzt4YO3Ysrl27Jo2uZGRkYOLEiVAqlVi/fj0qVqyIixcvIjExEQMGDMCwYcOQlJSEefPmQRAE9OjRAyEhIWjVqhWOHDmCSpUqAQB69eoFDw8PREREoFq1amytGYZ5BnEPxFXk1funw/h8/TmMXv0f3lt2HHqjGZwgAwDUeeU9RPT7Siqr5TgI9/5vMBhgMpkh1zoAvCCV2bptO/65ly/kYeq+VLfA7edvn8Wha7sBAJl3knB6izXpWU5Ojk05rVaL48ePIzU1FVu2bCk/WU+Lcj/nhx9+oGrVqpFWqyWtVkv169enjRs3Ss9fvnyZunXrRm5ubqTVaunVV1+V8jyUxD0jpvwxmS00eM4B6jt2M41ccpzSc4w2z+fmA1m8eDHt3r3bep9Tq6XrN27T3ME7KDKsNdWu/RJFRkYSEVHPnj2le5ozZ86kDh06EMdx9+a3W+e4h4SE0KZNm+jq1as0adIkAkDOzs4F3if1bfIqKRQKmjhxYoFlOI6zuZfarl078vHxoQ0bNlDbtm1JpbLej23fvj35+/uTTCaTys6aNYtOnTpFbm5upNFoKCQkhDQaDQmCQAqFgtauXVsWbwnDMIWQG/Mhl8tp8eLFFB0dTY0aNbK5Psg9Q6hCy97Ufd5+avXdblI7uhI46/XCs2JNkmscbMtzj47bcHD3IIVCRrI85RRyxUPLe3nYxri1at6WAFDlilVIpVRJeT/8/fxp0qRJNHnyZFIqlSSTySgkJIScnJxKNL9RUT6/i9T5WL9+PW3YsIEuXrxIFy5coP/9738kl8vp7NmzlJWVRcHBwdS9e3c6ffo0nT59mrp27Up169Yli8VSIpVnyh+T2UK9Jm2nFmM30s1kXYFl5syZIwWcAqCffvqJbsZm0MzB2ynUuwYFBlWUOh8mk4latGhhE9ilVCpp5KgvqV7FtqRQqkipVJKzszMpFApycro/nY3jOKpevTqNGjXq/uvtHKlbt26FDlKVyWQ0YcIEslgsNvVQqVTUu3dvCggIkE74gQMHEhFRQkICAaBp06bRxYsX6dChQ9Lr+vTpU2rvBcMwhfdgQHxuEGn9+vWpWrVqZOdo/bLy+uuvE5E14NTV1ZXkctsptXkTgZX2w9vbm0J8g2yuX7lfpjp16kSjRo2itWvXPnudj4I4OzvTzz//TFu2bCGe521+aVpaGnEcR9u2bSv0/ljn49l3LTGL+k7ZSb0/305nbqc9tJzBYCBBEKSTYO+R2zTl/R1Up2Jr6tKlS4HlGjduTKNGjaJT5xIosmJratCoNS1ZsoTUajVZLBYyGAzWbyGenjRq1Cgiun9RyX2sWbOGiKw5R3Avatzd3Z0UCgW1a9dO2g5Ail7ned7moqJSqaQRkS5dukhlTpw4QZcuXSIAdObMGSIiWrNmjfR8q1atSuioMwzzNB68HuXObunXrx916dKFXh/zLQGgV155haKjo2nQoEHk5OREN2/elK4Nfn5+NteaB2ekAKC6detKnZTckVOVLHfUQ55vBNbe3r7AjsbHH39MtWtbZ9Oo1WoaN24cNWvclFwcnWnyx59T+3btqXfv3jRmzBiKiIiwaWt56Hw8ccyHxWLBypUrodPp0KBBAxgMBnAcB6VSKZVRqVTgef6R84oNBgMyMjJsHsyzLcjNDjPebwiVoxLfLDiCQ1eSCyz3YAxIk7q+kDmJuBJ7EqEOrrjw1xZc/Gszrm/ciSrBoVjz0yKk3olD+pVryDh4CBdjT8LH0QFnj+6GaDFj2+qF2P/vYgg8j4z0FBy5ehwTdyzDt3vX2Pxemewy4uI2wGCyBmuJooi0jAy069Mfvi9FgpPJAY4Dx3GwWCwAAF9fXwwePFjah16vx/jx4yGXy7Ft27Z7+5Xh22+/tVlbJiMjA3379oWfnx+IyGahPYZhyo+816PcnB8GgwHLli3Dhg0bcHLNHAS6afDP+r9Qo3o17N/+L74d3gW3t89FpUBrIOrt27dt9imKYp6fOKhD6+N49GUAABHBbDYDAPTWf2A0maTncl+bN6g1r++++05a3M5kNOK/wycQHlEJKempsMRnw8nREfv37y+/q9sWtWdz+vRpsrOzI0EQyNHRkTZs2EBE1qFmBwcHGjFiBOl0OsrKyqLhw4cTABo0aNBD9zdx4sQCe3Vs5OPZl6k30dD5h+jNT7bQjaSCb8HkjQGJjo6mro3qkVphT1P6rpZiQFrX7EVvt/yUZIKcqgU1IoVMRRV9apFKrqGF3SpQiDNHgY4ctW+hpfY/hVNwiHXuPCdw5NbJjVShtvPmX6qrpg69Aojz8LbZrurUkzg7e4LGjsDzpHJ0otatW1Pbtm1tRj7keb6dVKxYkTp37iz9bG9vT4GBgXTr1i06ffq09BqtVkvVqlWjESNGlO6bwDBMoeVej2bMmCGd0xqNhvbs2UMD6qiI50AedhylT/Si1Ik+tGWAO/36mhtNbnc/F5FGDtLW1pJMJuT/bON4giDPt51X8OQrl9Pqzj0pwMM33/MapZoa1Kwr/fxhv2EFfm6G+QUTABrT5F1SCHLiOI4qVKhAqampNu1EORj5KHLnw2Aw0KVLl+jYsWM0btw4cnNzo3PnzhER0ZYtWyg4OFhKttKnTx+qXbs2DRky5KH70+v1lJ6eLj1u3brFOh/PkUy9iQZ8uo1mbLvw0DJ5Y0Ai69alZZ/3J9MEVzJNcKM6Yd7U65XuZEiOoxlfTyZ/X18SeJ4UchnJBYE8XeypZ7MqVCnIi5waOVHVxVWp8vzK5FrRzvbeKwfy9LIu5OTj402dO3cgKJT5Tl5BEMg/KIhUXt6kcnCkkJAQunLlCm3evJlUKhU5ODjQu+++Kw2XchxnE2cCgK5evUpERK1atSKZTEarV6+mcePGkUwmYzEfDFPOzZkzh3x9rR0AZ2dnOnz4MBERWbZ/RTwH0mg0Utndu3dT5cqVSanMfy1xcbej4ODgfNu1Wi3Z29uTl5fX/bLOGlqxwp/mDhtHcqGATkueB8dxtGvXrkeXAUgpKIjneDrxyQZKWh5Duv8SpHqXh84Hd68iT6xVq1YICQnBwoULpW1JSUmQyWRwcnKCl5cXPv74Y4wePbpQ+8vIyICjoyPS09Ph4ODwNFVjyokhU3ZD4WOHWf1feuQ0trxSkuJx4Y8JqBP/J4yQ47JdTYhye/hknoaXaM0TYiA5dGIgTOQDJWfAcbWA3x214MCBYP2zlnNy6KHH0f9O4/ria7Czt4NBb4Jeb7Cu2OTlBzH2JgDAw8MD7dq1w44dO6AzGqHPzITZbASRdfhTpdLg4MFD6NGjBzp16oSLFy9iy5YtNkOrCoUCFy9exIQJE7B06VL89ddf0jx+Z2dn+Pn54cyZM8V1aBmGKQFZWVnQarUYN24cpk6dCgAw75uG8K7jkUVynP+xBcjmUsYh+K1tSNeZsX5iJD51SIXaVYUrE28g+WYG/CooceuqAZ1f9cSWfxJgNgIVwp2QcEeHrAwjiACeB1yd7FDJS4N90YkY0aY2/oi6iLvp9267cDxAIjiZDNXeHYVLa3+DPiURglINTuBhykiH3MEJYZPmwj2kMq79MgvJx/aj5bSliF/9Ky7u34iM9ERUqFgRl8+dxbp169CtW7diPW5F+fyWPe0vE0URBoNt4pTcZC07d+5EQkICunTp8rS/hnmGtWsXin//OIfZWy9iRNvwQr3Gxc0TDd5biLibo3Btx8+wiz8Gte4mLjg2xrWQJnAIa4hJS29AoZGjZdMgNA5zRws3DRqYc5BqTEOaPg0J2Qm4o7uD6/GnUNlOhxSzFr+sPovsbBN8PbX4aGRrjF91W+p8BAUF4dChQ0hKSoIgWO/Hms0iZDIgsp4GrVvb47XXGiA5WY9mzXMQHNwOmzZtsqm30WhEy5YtcefOHYiiiO7du0vPWSwWpKWlQSaTSevPMAxT/uTGHl6+fFnalqjU4XYGwSIa4f3mZlTzluH7Lnao62fNqNw6mMefZ4CrJ8+hRVtPbD2ZjqQb1v3cvmb9jPz3z3i4uAgY870vtv6TjisxRoADBAFQKWRwttcgwyyHXODx94nL0JtMGN2qBe7UaoblP0wH6bIgUyhx9ufvUH/4ZxBNRlzc9CdSb1wCAET2H47K4dVhMJtwMmoXKjZti+t//YTL+zbA8cNP0UHpB7PhIi5/Ng5Xr14tzUOaX1GGVMaNG0d79uyha9eu0enTp2ncuHHEcRxt3bqViIgWLVpEhw4dosuXL9OSJUvIxcWFRo4cWWLDNsyz4/O/ztDQsVvox92XKeOB3B9FFZeeQ2/PO0BvjN1M1xKzCv06URRJp7tGkycPJG9vR5LLePIMCSOv2o3v3ZrhSKZSk727N9lpeHJxkZGLi0CCAOJ5jhwcePL3lxPP37tPy3FUr169Rw5/PvioWbOmNAvmQVOnTiUALC6EYcpY7gw5hUKRJ+dHZQJAAQEBdO7cOQoNDSWlUknx8fFERLRp0ybSaDTSLJfcqboAaPTo0VKsWM8+rnTt2jU6ceKEdF1YuGABnTp1imrUDSTwoI4dOxJgnZofHR1NtTu0IOHeLDyFQkHh4eE0btw4EkWR3nvvPWlmzPz582nv3r3UokULKdbD29ubJn0/kyqt2UcvT1tKx+793tq1a9PJkyfpxo0bxXbcSizm45133qHAwEBSKBTk7u5OLVu2lDoeRERjx44lT09PksvlFBYWRt999x2JolhilWeeHfEZOfS/5Sep7/jN9NYnW2nG5vNkthTtb+NGko5mbbtAfT7ZSv0mbqft5+4+db1iM27Tmjt3qWaP1+4FqQrkFlKR6jfwIq2dnHb8NoBqR3iQr4eGmrzkRXIZR71e8SAvOzfi7iU5a9asGTVq1MgmsOudd94hBwdrwiEHBwdq2LAh+fr6kiAIdOLEiXz1OHLkCAUFBVH16tVZ54NhyljutNuBAwdK8WgajZI8PGRSGoCmTZuSWq2mqVOnEpE1/iM3VsTOzo6USiV5eXkRz/M203ELegiCQK1btyZnN2sH49/1f5NKpSJ7e3uSy+Xk5OVOan9/qXxISAi98sorNHToUHJ0dJSm78pkMnJ2dqY333yTYmNjiYjIxcWFwj/5knqNmlfg7+7fv3+xHbdSzfNR3Fjn4/l2Ny2Hvv7nHL0zbgsNnnOAlhy6TpcTMh/aSc02mOmPozdp6Mz91GvsZuo9fjNNWXeW0rKfbvSkIDaBr5GRUqDZnDlziOcffuGQyWTUt29fio2NJaPRSJ988omUCbWgh7Ozs9Qxedijfv36xd4+hmEKLzIykoYPH05EuZ0RnrRaXupsEBH169ePOnfuTMd2fU2b/w2j7TuCaehAX/JwV0vXhnr16t3P/8Hdz/+RNzmZIAjWjoObNaeHn5+vNMPuYZ0WtVr90OvH+++/T0REWxPTKKBhG3L2qUDvTvmDWq+Ook2bt5BarSaFQlHsx6xUA06LGws4fTHsv5SEVRsvIDkuCyIBWrUMbqEuCAt0gkLGQ2cw41Z8Fm6fSYDRJMItyBGtGwTg5UoesFc+dahSoa1atQpvvvnmA/P18wv0DcDyX5fg7+0bMGPGDJjuzdd/FLVanW8dhgeNGDECM2fOLEqVGYYpBqtWrUL//v2xcOFCBAUFoXnz5lCrOfz0fVO4uqjw7Q+nEHvHCIIR8xZ4IiZGj6QkC4LdqyDFGINJk+KRliZag0k5QCSA4wAi6/oxHMflC1Y3m00QRetHMsdxUCgU+WIqH9SsWTMcOXLE5lqiUqmwYMEC7K7WCG67LuOPFVNx++R+cBwnrUu1aNGix15/iqoon9+s88GUqSyDGUevpyDqUhJuxSQjPTUHFiIoZTzs7RSoUMMTr9ULgL+LptTqNG/ePEyfPh2xsbFSEqCy0qdPHyxZsqRM68Awz5Pc8zsuLg41atTAnDlzEBkZWWDZWbNmYeLEiUhPz12ZW8DIj91RLcQZ4z67CV0Wh5wcEfZqB9xJSoPeaEBhP1LVahVycvQFPqe100CXkyN1RB6Hl8kgms0QZHJYzPe/+NjZO6Fq3RYwv9sfyxrVhL1MgFarRYsWLXD69GkIgoBatWph1qxZqFu34AXsiqJIn9/FPu7ylNhtF6YsrVy5khQKBQ0ZMqRIgaQl9WDp2Bmm8ObOnUuBgYGkVCopMjKSoqKibJ7PPb8XLVpEp06dojp16hDP86RUKql69eq0adMmm/3k3vLIzeOhvJc4TOA4quDqRi8H16caXpWoulc48bifSp0DR4FOPo88t7UKu0c+/+CaMdWqVXtsuYiICJtbMi4uLuRg70Ct6jWnBRNmkclkoldeeYXkcjn17t2bLl26RBMnTiQHBwe6ffv2Ux9/FvPBME8oMjKSmjZtWqaLQ+V9sKRkDFM4eTsW586do4EDB5KTk5M0G4Xo/notRERjxowhHx8fcnFxodGjR9MPP/xAKpWKpk6dKu3HwcGBKleuTFqtVgom5TiOGjVoQH27vU4cOAr2DyIANLT/AAoNCiYPd3ebc1jgBWraoBF5eXgW+rxXq9VUt05tm20VKlR47OsaNGhAgHXtqdxO1SuvvEKBgYE0fdgXtGDBAgKsa1/lzXpau3Zt+uSTT576PWCdD4Z5AgaDgXieL3AxqLJ4uLu7s5kvDFNIeTsWRNZVZ318fKQA0QcXjvP29qa5c+dKC8cREfXo0YNcXV2l/bi4uNCPP/4odVIEQZCWFnnn9X7EwRoQ2rRpU+rduzcBoI8++sjmPK5SpQo1atTIZlXsvA+e4wv8slMcX4A4jqOAgABydnYmuSAju3tTgVeuXGlz7Bo1akTNmjV76vegVBaWY5jnTVJSEkRRhEqlKuuqAAASExORlJRU1tVgmHIvdyG4Vq1aSdt4nkerVq1w6NAhANbz22KxwNPTugicwWCASqWCp6cn4uLiAABKpRLJycnSftq2bYuZM2eiTp06SElJQdWqVWGxWJCeno7TMWfRNKguiAg+Pj5YsWIFAOCnn36Cq6urVI/o6GhERUXZBKHnzfQsklhgnIi9vX2h2v6oZIVEhA4dOiApKQnHT57A3E++Q6h/MKZMnoIbN27AYrFg6dKlOHToEO7evVuo31dcWOeDYe4xGq2r3GZnZ5dxTe5btmwZZDKZtLouwzD5PdixyJW3Y/Ggtm3b4vvvv0dqaiqICNu2bcO6deuk1wHWgFNPT0/8888/AIDTp0+jY8eOUKlU2LtqGwKcfAAAhw8fxrJlywAA9erVQ3Ly/ZW8AwMDUatWLdy6dUvaRkT46quvAAAq2YNfdqwdk8zMTJutFfv7F9iO3GtDoO/953mOl1aV37BhAyZPnoxq1arBPzIM3bt2gzldj6CgICiVSsyePRu9evUCz5dud6D05iwyDFNkFSpUwPr161kqdoZ5Sm5ubhAEAfHx1rWhZs2ahYEDB+KXX34BAPR97VXU8PdG1KVrWPv15zjl6Q4A6F7BE+nXA3Di2k0EuDpjw4YNAIDKTcLgqtYCAPz9/NG7d28AQExMDOzs7KDT6QAA169fx/Xr1/PV59NPPwUA6M0PznjJHQXh8vwfQBV1ge0SBAGiKKJ/t974+Y/FuJMYB3cPd8THx8NOY4fIOpH4ctKXsJjM8CZnNHKsjir9QlCnW2O4+rjD29sbr7/+OoKDg4tyOJ8aG/lgmHsUCkVZVyGfmjVromrVqmVdDYYp1x7sWOSKj4+Hl5cXAOv5XadOHezYsQPmFD0cshT4Y9FyeHt5YVj/Afi0XRv4Vwix7q9SNdRq1xm12nVG3Y7d4O5nHVW4lZIGmSAg0NcHAa4e+O+2dV2ofu7tcOGjLYjwCEVrz3oQDfen6PPgoJQ9/tqiUqmgVuXtYNjeirk45mKBr7NYLCAiTJr3Ne4kxkntBgB/L19U9gkFz/NoEhaJ4LAQWEhEqNkTYT4V4O3tjdTUVGzZsgVdu3Z9bB2LE+t8MMw9uQsilhdeXl4ICAgo62owTLmXt2ORSxRF7NixAw0aNJC2ffTRR/hp4Y+Y03cSDk5ej3davAFdSibese+Ejn5DsWn/QdjZ2eF2tgH1e7wOzjcIt0UBpy5ehiAIUKvVkMnlaNi0GYZ9MBEiEWQyORbH7kJUEKFXVRWWnFyHHLM1MZhKLocIgtnyYNLB/Kt7G/R65OiLJ+mXTCZDREQEvp87Eyu2/Imu3bqiZd+OaFSjHrIvpeDqlWu4fvU6tm3bhpdffhmVKlXC22+/XSy/u9CeOry1mLHZLkxZyJ3Xj3IwywX3ZrowDFN4K1euJKVSKS0EN2jQIHJycqK4uDgiIurbty+NHTWGvmw1gnwdPEkmyCgksAKtmPMb/f7RdGoUWJuUCgU1bNhQ2k/Hjh3J3t4+3/nZrl07evnl1iRwHGm1WmlmiUIuI4GzLevh4UGCIEg/y2Qyql69ev6ZKQoZcXKZ7bYizmzJzfmhUqlIqVSSv78/vffee5SamkoZB2/TrbF76ach0yk4OJgUCgV5eXnRsGHDKC0trVjeAzbVlmGKIG9+AP88izeV1UMQBNJqtZSVVfgVexmGefj6TEREzZo1o369+9KtsXspcdEZ2r17N1WuXJmUSiU5OzhRzypt6eSWPTb74XmeFAoFyWTWTkFAQADJ5XLieZ6Cg0OodoAPhYdXIi8vL+n8dVWDZn/xIbVs2dKm05H3kbv67UM7Enb5OzyPeqjVaoqJiaEVK1aQQqGgc+fO2RwXQ2wm3fk6iu5MO1LkxV6Lgk21ZZhCmDdvHoKCgtCrVy84OTmhYsWKuHPnDrRabZnUJ3f6nb29PTIzM3H8+PEyqQfDlIXc81GlUqFevXo4cuTIQ8uaTCZMmjQJISEhUKlUqFGjBjZv3ozhw4fjxo0bMBgMeOuttzBw4EA4ODjAwcEBBoMBr/d6AwCgquyKZs2aITo6Gnq9Hmf/2YeZnT6B9734kNz9WCwWGAwG3LhxAwCwcuVKGI1GWCwWfDr+C2jVajg4OODu3bsgIty6eh5JYxzQ8uVmWLFiBTp16gSe56WAcY7jIJfLcezYMQwaNAiQKyCEVoLnzpMQ/ALA2dnDbdVmtJr/K/xDw+Cg1aJ/7954q29feHrdm8kjADV+qYrGc6vgrR6vQqvVgohQpUoVDHp3IOaN/RbOF4HkZTGIn3sSdyYdQsLskyCzCJdXK9pM8y1LbG0X5oW0atUq9OvXD3PnzsWQIUNQsWJFnD9/vtTrwfP8Qxet++GHHzB06NBSrhHDFI+irKGybNky9O/fHy4uLkhLS4NWq4XRaMSVK1fg4eGRr3yzZs2wd+9edOnSBTNmzMCWLVswcuRIHDx4ELVq1QIA/PPPPxAEAWFhYSAi/Pbbb5g+fTo29f8ZVatWheCiskZecIA+ORN014i9hr/gWMHaAeE4DuA4cABMZjO6f/w//O+dfmhYwxoAfvK/aKzdthVZMjV693gdAAe5KQO1dPthUTpC0HqA4wCjWcTNpDQMW7QVPl6uiEtIBcdx8PLxgbsgICs1FW169cIvixahQ4cOWP3HH+AFAX+vX4++ffsiKysLAKDVatGjRw+sWrUKt3/4EwnTRiHiQsHXrLGtBuPDjoMgc1ZAcNdAFegIVSUXcELJdjyK8vnNRj6YF9L333+PgQMHomPHjhBFsUw6HgCkSHy1+n6Uu1wuh729PUaMGIFz586VSb0Y5mmsWrUKI0eOxMSJE3HixAnUqFEDbdu2RUJCQoHlR48eDaVSicWLF+P8+fOYNGkSsrKypFwYeR09ehQHDhyAj48PKlSogODgYAwdOhQdOnTAd999J5Xr3LkzOnTogLCwMFSsWBGTJ0+Gvb09ojV3IDgoALMI0SRCNFggUyuRokiAwlmF7PRU6FJTkJmShMykRGQkJSInLRUVvD1x5L/TSE9MQHpiApSciMsJSfB1cYY5NRHm1HgYMrNwy+SOVL0CSYlpSExIQ1pyBjSiNcQ0I12HBrWq45Oh72BAl3aQWQxINRrw1/r1OHP2LNauWwdBLgfH8+jWrRsyMzORk5OD27dvIz09HZ6enggODgavtc6eiQ6vhJjaTXF92Gqk/HMZ5gwDWrZsidRggteHteHWvyqcOwRDXcW1xDseRcXyfDAvnNxsiOPHj8fff/8NIHc5a/NDRyFKyp07dwDAZmlrk8kEs9kMIsLBgwdRpUqVUq0Twzyt3M597gyKBQsWYMOGDVi0aBHGjRtnU9ZoNOLu3bsYOHAgOnToAAAYNmwYvvnmG6xbtw6zZ8+WymZlZaF3797QaDT5MoCq1Wrs37+/wPpYLBasXr0aOp0OLQd3gVtERL4ynqiJ6uj58EZVroX+/fvjzWEfIDIyEn+O/hhGsxnL1v8NLy8v9OvXD76+vnh36s8AgKioKMTGxqJmzZqIjY2Fdu1hAMC/23fByckJoihi2gI5RAK+CnJE1PDXEcUBshwTQuOMkMt4JDsLgJ0axHE4S4Sl+8+gmZcrzs0bD1cAgntlkNkA+4aecGofDE7gIIoiDAbDo9+gcoB1PpgXyrx58/D111/DYrHgtddes0l5XJ4QEWQyGRo1alTWVWGYIsnbuc/1YKrzvHKXEHhwqrudnR2uXLkCo96aM4PjOAwd+h7at++AhIR4rF+/HqmpqdKU2rVr1+bLBHzmzBk0aNAAer0e9vb2WLduHSIK6HgUxuuvv47ExERMmDABcXFxqFghCIOaN5BGL2/evGmTJVSv1+PTTz/F1atXYW9vjxo1aiAqKgp///03IiMjMXPmTBgs1i87Yw/G2Pyu0TVD4VTRHRnJOgQ5qpCi02PlySuw8Bw6RgYjUS7DOZdsHPzvPOyqKDCmoT/uRJ/F8uXLsXv3bmzZsuWJ2liqSizs9Qmx2S5MScmd1dK3b18CQDVq1LCZYVK7du0iRZgXxyN3qW6NRmMTGS+Xy2nDhg1lfcgYpshiY2MJAB08eNBm++jRoykyMvKh5YOCgujixYtksVho69atJJPJiOM4mjt4B80dvIPeavkJebtUoBkDNtHUfmvITulAgHVhNg9HP2papSvJBQUtm3iIstL0RGRdTO7SpUt07NgxGjduHLm5ueWbCVJYudPxlUolRUZG0uLvvqFZfXsWWNZoNNIXX3xBwcHBpFQqqXr16rRp0yab2Th+fn7k7u5ICrlA7u7u5OrqSt26dZP2kXc2jqurK/Xt25diY2PJbDHT3KNzKPKXl6hWZBVSualIrpCTu7s7tWzZkrZu3fpE7SsORfn8ZgGnzAujXr16qFu3Lo4cOYJjx44VGNAZFhaGS5culUn9XF1dpZku/v7+iI2NxZ49e574mxrDPExRgkFNJhO6deuGrVu3wmw2Q61WY+rUqRgxYoRUZv78+Zg/fz6uX78OURSh0+mkFOMcxyEsLAyRkZG4ePEioqKibPb/1Vdf4bPPPoNCoZDWV+I4Dm5ubkhOSsa893Ygop0D2r/WBD5e/rgTfxtKhQo5OTpwHA+zxYwg/2AE+Yfg0pULGNVxIXqMroNLsf9h+vTpOH78OO7evYt169Zh7ty5CAkJwcKFC4t0vJb/8gveHjoUs8aNQ92qVTFvxQr8sXkTRrVpgjf6DAB3b8QjN0j129+X4u+9+zD5vaEI9vfF/pP/YcqiX/HnN9NQJTQEHMeh/4SJcHYluDoo0abrG5g7fymuXL2BtasWwE6jBsfx1oBXjgcHzho0wgGnLDdxcP8eZArZUJICLmYHtO/5Opr5NytSm0pCUT6/2W0X5oWQOxQ8atQoLFiwAKGhodi+fbv0vFKphMFgwJUrV8qsjsnJydKCVCkpKYiIiMCsWbOKfKFkmEfJDQZdsGAB6tWrh5kzZ6Jt27a4cOFCgTNLevbsiY0bN+LDDz9Eu3bt8OWXX+LDDz9E1apV0bJlSwCAn58fvv76a4SFhWHq1Kn49ddfodPp8NFHH8He3h5TpkzB1atX0bBJc0z8+yw4joPAc4i7chYr5i4Ax/MwGo1o1q0vQqvWwu6/luLK2RNQq7UgHkgx30R2TjauXL8IjuOQna2T6sdxHIaPGIoPP/wQb77eBwBAIkGn06FGjRp455130KNHDwB44niIr4cPxyt2dmj2x2rgj9X4mAhrOODotVvQ/rk0/zHevB0tK4ci/eIpnLx4CnYAKrq7YOL30/FmfetsnC4h3gCAWLccfGX5GeY3zLj7QSLe3DwKduF2D61Lq7R60GkMGNntE3hpvOCodCxgcbryj3U+mBdC7qqXSqUSFosFffv2xaRJkwBY70cbDAbwPI8TJ06gZs2a0us4ngcVQxBq8xaOiL2dA3s7HidPPriQ1H2//vor3nrrLQBAixYtnonAMebZUpRgUADYvHkzmjZtihkzZgAAWrduDTs7O4waNQonT57MN4py9epVKYC7SpUqGDBgAM6ePYt169YhMSMHc777GvroXdCnJQDg4N+qH1K3WBd3u8p54sy2vUi7chkAkJOTiXn/fILAK04YMGAAPvzwQwBAkyZNwPM8UlJSMG7cOPz9999Qq9XI0mUBjoAoEvbu3Yv27dtLSxQsWbLkieIhjEYjovV6DHRxBQAELF4MmYcHOnz4IZJTk/HWuC9AZI3TAggQCZM370OTDl3wZqfOILJePw6mfYEjp8+g1/tjQKIIIsL5rKuooDKir2MAbt68jW4YgqlVP0JIsD8IBCJruZxT/0HcehYcL4NaTEG9dWvKTb6OJ1ayd4CKjsV8MCUh977y33//Ld2P/vzzz23iL9zc3OjkyZN5tnGPjdngNXyhYjvkD6RNzn306fMaERGNGzeO9uzZQ9euXaPTp0/TuHHjiOO4Mr1/yzx/DAYDCYJA69ats9ner18/6tKlS4HlAdCwYcNstleoUIHkcjm5ubkRYE0ZzvM88bzt+TB58mSKjo6mkJAQ6/lyL66J4zibf3EvS2duDJTNOcZZX9O0aVPp92u1WimVuJOTE/Xt25e6d+9O/v4BNHfwDroZk0zvvPMOBQYGkkKhIABUvXr1Jzqfcq8dywMCKTq8EkWHVyKih8ewEBH16tWLIiIibGJY1Go1KRSKAstbLBbq2LEjNWrUqMDnM/ftpwtNX6Xz9VqQMS6+yG0oLSzDKcM8IHfVS4PBIK1+mTcaHwDS09NRu3ZtANYso01qvQJ7lQO0dm6QK5T4eNgAtKrmDWeeR+4alWL2/VERmVoJ8DwgyPKtG2Uy3V/lsvnLFbBxUyds3xGMmTPfAwAkJCSgX79+CA8PR8uWLXH06FFs2bIFrVu3Lv6DwbywckcA9+3bZ5NNVBRFxMXFFVgesCYBCwgIgFKpRHBwMK5fvw6TyQSO48BxHHx9fSGKYr6p6p999hkiIiKk25mixQII8nujBICjo6NUNicnp8CRPl/3UADAgQMHpEymHTt2hMVigbu7O5KTk9G3b19s3rwZ8fHWNnAch19++QXXr1+X9vnFF18Uy/nkOmTwY8vMmjULYWFhqFSpEhQKBYYPH463337bZjZMXsOGDcPZs2excuXKgncoWuDQtibAqXDttWFI+3fDU7SgfGCdD+aFkLvq5d69e6XVL2UymZT2GADMZrM03S87OxsJd2OQY8qGyWyAjJNBm9UQRy6nIF0UYQQg4zm4urmB4zgoFAoE+fqDA4FTa6zf2QrAcRz27b2J4AojkZJiRs69aYR5L5QJCQnYvn0763gwJWb27Nk2CcBWr179yGnn2dnZiI2NhcVigU6nkzoPiYmJaNeuHRQKBeRyOerUqWPzOlEUwXEcVKo8MQkWa6clKCjIpmzecxGwBmADQHyKNbX5+PHjMWTIEHTv3h06nQ5KpRJJSUkFfrgX5w0JNzc3CACSzNZz1ePerZ/4+Hhpmu2D3N3d8ddff0Gn0+HGjRs4f/487O3tERwcnK/s8OHD8e+//2LXrl3w8/OTtpsSEpCxeQtuvT8Kdz//ERlbToKTawCOBxmMxdjCssFiPpgXxsiRI9G/f3+88847+PHHH3H27FnI5XKI9+6/ElmD1ARBQEWvKjh/58y97TrUrFkTP+2YgCwyIfe7nVJth+x7F2K5XI7Lly9DkMtgycp4aB2ICBaLBZUqtQAAzJu3F++917IUWs8w93NptG7d2ibmY+nSpcjOycY3R7+ByWKCjJdBxsuAe2kz6naqi97je0OfroeTqxPeqfUOOI4DEaGyr4itW6+gSa1KOJUn3TfPcVAq5XDS2iExJQNqpQI5BqP1w5NEXL9+3aZuuTk6mrZsjb07tkGpsmb9ze3oVA2thM4dOmH6tG+wfft2HD9wBF5e3khOTYWvtzc+/WICAvwCrTsrxt6HQqFAhEqFw9k6tLq37lNubpHhw4c/8rUqlQq+vr4wmUxYs2YNXnvtNek5IsL777+PdWvX4s/+70A+YwFu5pghGsywpOtgSU0HAMg8neD2/ivQNm8G47XrUAT4Q/ZATpRnUond/HlCLOaDKUm58+wFQSCFQkFyuZwCAwPJ0dGRAJC9vT0F+YeSp7OnzWqWuQ9exROv5gk8yE7x6JUprftTU5MmteiPP6ZSw4bVaODAbhQfv4ni4jdQQuJ2EkVzWR8S5hn2YO6JqKioh5Y1Go00YcIE698xz0u5JywWC2k0GgoMC6QK4yuQ50uepHS2xl7UHFOTwIOcqjhR4xWNqcGyBuTdw9vmb9xdY/33jSr3z5XcpeC1ClB1j8fHTtk8+ILjqLpEvnsvl4eSHDWuUv6PuYN30PfvbCCNUktqhT3JBDlVDg2nTZs2SW0HkC/OpSiW/fgjKTiOpnh504m//6ZBgwaRk5MTxcXFERFR3759ady4cVL5w4cP05o1a+jKlSu0d+9eatGiBVWoUIFSU1OlMkOHDiVHR0daWq8F7W/QmQ40bEPH+g+mSyPHUdz07yh90yYy3tv/s6Ion9+s88Ew9+R2TGSCnMICK9Poj8bRn4s30cSJEykwMJBq1KhB7057l0ZMHkFD+w2kYBdfkvE8cQ5O5NquC0058h8tu5NEnjtPUrLRlG//zZo1oxEjRpR+w5jnUm7SvEWLFtG5c+do4MCB5OTkRPHxBQckjhkzhrRarfRh7urqSnK5nHr06EFKpZJCIkIocGQgRVSJoB49elg7FG+8IQV2urm5UceOHYucSE/quPNF7IQ85tG8Rj1aMvpbWvj+l+Tt4k48x9O0XsNoZa22NGPcOFKpVLRixQopiPz777+nkydP0o0bN57oeH/i4UneMhkpZDKKjIykw4cPS881a9aM+vfvL/38sARheT2sXYt+/vmJ6lcesCRjDPMEbl9IxcaZJ+EicNBUcYW9swoWiwjRLMJsEnE65jhy1HdhlxkAPuEvyASg19TpuOXojl9uJ+LvhDSY7p1O0Y2rwkXO7moyJSc3ad7cuXMBWG8F+Pv74/333y9wyqyLiwsyMjJgsVjQv39/rFmzBllZWXB2dkaHDh1w5MwRKEcq4bLIBRUqVMBvv/0GZ2dnDB8+HNOmTZMSgOWSyWQwm835fs/DLFmyBH379oVKIQC8HIA1P8iVK1fwNB9DdnZ2EEURn376KUb27IlrXbshaNVKtH3/fezbty9f+f79+2Px4sVF+h1Z+w/g1rvvAgDCT54An2chyKdlydIh/utp0B2+CYWfHfx/nAFeoXj8C8shtqotwxSRKU6H+L234SBwiDcT0uKzcedSGpJuZiItPhu6VAO8NBXhmhQJlcELCsch6Pv9Yrj5B6KWgwZzIwJxvEEEPgr0REd3Rzg8EDzHMMUpN2leq1atpG2PWj8FsH4wNG7cGIIgoFu3bkhPT4darQYRQRAEOLg5QMbJsGfPHunD+ZVXXsGkSZNgMBiQnp4u5ZZwdnaGVquFr7sS3L3fnVeFChWkOjk5OQFAnkXfOBiNRimjaW7Hw9PTE+PGjUO1atUAWDs3ACB3dgFgjVfp0qULxowZg4iICPTo0QO9e/dGVlYW1Go1PD09gdy1XQQZAgICEBgYKMVz5T6K0vGwZOlw59NPpY6HQ8eOxdrxAABeIYfhUhzUEe4IXDzvme14FBX7asa80Iy3M2FJN0DuaYc6A6uhutECueLJOg4eSjnGBnsXcw0ZJr/cKbOenp422z09PXH+/Pl85Y1GI0RRxNWrV1GlShVs374ddnZ2MBqNMBgM2LF1O0LbhSKZUrDzxD+QCdaRidSsJJy4eBAyXkBKUrrUURBFEVlZWXijFo/5iciXiC8lJUXqqKSlpUEmE6RMvXqjdbQkIyMT4O53WpKTk6H1C8CZM2cAQBpVMaWmWOuSkoJzJ07g1JEjaF63Ljbt3o2vP/wQuqNH0fKll/Dt5Mmo8cEHUBNhZ9ThAheaK6rLzZpB1OnAa7XwmfY17Js3f6r9PUgXdQTx0+fDnKKH29A3i3Xf5R3rfDAvJHOaAcZbmVAGaqHw00rbn7TjwTDlTtwZICcNAJCUkAwiQpCXC/YfO43Tp09jzR8rEBbkh/NXbiArNR1Z1bIAAD3f7weZs/Wj4a/N/yDK+RiII5hT7t9iyeKy4NbDDRu2JoDD/Znluf/PykhHoCOH62nWTonZXFAngJCRbq0f7+ML851YfDL8vYc2xyKKuHL7NgDg93/+wYdu7miwbDluLluOEWYzJiQmot5HH4EDEPzll3j77bexaNGiJzt294g6axp3h3btoG3R4qn2lVf20aNIXLAExquJkPs6ImD+OKjCw4tt/88C1vlgXjiWLCPM8Tpoqj0H09WYF1Ju0rz4+Hib7VLuiawEYEHj+09kWjsB06pdQq029vj2oBE/Hk/B+Ssp4AD8078S+IShSE+zYGzidLiZnbEbSQh09MHV+bfyxWQMePdNNGlXH8vbXYPTL5twM/om0tIypU6IhYDraQS5Ug6L2QLRIoJT8HDxVkOfbkZ2uvV2i0apAS9wyLoTC4VSCZPJJI2iKFQqBNyLK7ltMsFsscDZzg6/DB6MuPR0fLJyJUIbdsIbjRrBA8AfANLOnMWtf/5Bgx3bMWH+/ALzahSFqnp16GNi4FaIxGKPYrh8GVc7d4Wyen2QnoOYngWZpxae49+GtlUraWG6F8mL12LmhWbJMsJwLQOqcJeyrgrDPLHcpHk7duyQtuXmnmjQoIE04oGevwDvn4DbqCPWzkqz6VB9eByfrjqNKzFnoLW3Q4irBvUC7ZGZnYjqxsrY1GMRlrz8HQBgXK3BODplNXZPX46YX7bC3dEFPM9DdzIDkXcrIV7bDpfOx0EUrbdY/vjjDwiCgHXr1uFcaixcNh1BcOVQVKlSBZ3bdcLQvh9BwWlQuUJNKORKzP/sd7hrVGhRrTp+m/w5rpw5bR2hCQqCUa9HDz9frG7cCJ5eXnBycsKYTz9F9+++w9Cff8bIceMw5+BBuA4YID08e/aAp1wOC89jzZo16Nq161MdZ7+ZMyA4OuJym7ZIXfXHE+0jZcUq3HhnPASPKjDfvgX75lXhPek9BK38EQ5t2ryQHQ+AjXwwLxAyizBcTYemuntZV4Vhnlpu0ryXXnoJkZGRmDlzJnQ6nTV5mOku+q3LgW/yRkyd8woUAMLDw/Hjyn9RvXE7xMbG4vPPP0d2jh6v1Q8BeAXazR6H1PgkXL56b2XnacC1tJvwOe8OR5U9ZHYAmQggwqqd/8LP5IGr4nUYMjIg11iDMH/44QfI5XJ8+eWX+KXJGphizsA30Bd7NuyCp6cnFi9eDJPJhLtJsagSUA/pd+xgEgUkpSVjx99rcXrnViSbLEi8ewcAIObk4EJmBpKSksDzvJQYrV+/frh586aUzj0qKgqxsbEI1enwX3Y2hvXpA1EUMWbMmKc6xnIfHwQtW4orbdsh/quv4Pz6a49/UR4ZO3YhedEmaOqHwGv8WMicnZ+qPs+VEpns+xRYng+mpBjjssiUqi/rajBMscnNTaNQKGxzT9w4RM0CBer/ejep7IQJE4jjOJLJZOTk5ERhYWHk4OBAN8c3Iv307tS3b1/q1atXgbkn2rVrJyXKmjZtGjk7O997jiMXb3/6/fffCQCFhISQvb098TxPE2Z/TQ5jJ5G9g72U2IznQUqljGrXri0l3Jo4cSKpVCpycnQgQeDJTq0itVJJfp4e5KlQkJznyc3Njdzd3enff/+la9euUZUqVUipVNKYMWOIKE9eDbmcnASB+rzxRr68Gk/jYvOXbRaVK4juyBG68/lXFD97Lll0OiIiutZrGF3vP4hEo7HY6lKesSRjDFMA/Y10suTkT/7FMM+dyzuIJjoQpVy32VxgZ2WiA+XMfLvIibK2no4l5+9/KrCzEhkZSZ6+3gS5nCJqVaXDhw9TdnYqbd8RTLVrh9r8HpPJRJ9//jmFhISQSqUif39/eu+99yg1NZWiWrSkA2/0ooyMDBoxYgQFBASQSqWi4OBg+uSTT8hgMNi0L+2vvyg6vBJZHtj+NESzWep4RIdXojuff0nXer9Pl7sOoNhPvyDRbKasqCi60Px1utCoK13qMIxSVqwgIqJrfYbQzfdGF1tdyjuWZIxhCmC8lQnBRQXBTl7WVWGYknV+I7CyFzDqEmDv8dBiZLGA+9IFes+3oBo6q0i/YsTms1ilNONgpWAEe+e/Vu+MPYU3LwKbqipRy70yMjLu4uixxnB2+h9q1x5QqN9xpFlzWAID0eD33wpVPnXlKsRNmoRK585KU32fBBmN0B06hFuDh9hs5x18IbgHQO4mQH/+JjiFHdTVAqG/nAK5lwbaFvWQsmQnHDvWgiVTh6z9l+HYqQ48Rrz/xHV5lhTl85vFfDAvDLmPPQxX0iBUZPddmedc6jXrv7eOAMp7U8k5DtKKa/c+mCknBxwAkyUQ3PV0m+fyLs7GPbiN43BNtE6f1dnLcDozWyqb+232vC4LgD2MOdeQkWFGenosAODu7RRE4zJEEiFarIm/RJFAJILE3J9FEAEO8fFAfDyuLt0IcBw4ngN43vp/DgDHW7dxHDiOg/HAcXDOroi7moF8fQ+pCfnblxafjewMIwQZD5mcR/LsmZDdiIbTved9Z85A/LcrQTnJ8Pl8KPQXL8IUtxuiIQPG26lw7FQXLn17g+M4ZO07gfR/o8Db28Gpe72nninzvGIjH8wLJed8CtSV2EwX5jn3awfgxoFCF080ToJBrF2kX/FSW+1jy3AkYh4GwBH3V3o+ebI9sjILN8399ZWrilQnAEhxqohTNUcU+XUAwMs4iGbrR6KPnINr2kUEu18DeAHZxy6DE5Tw/+FTKEOCkbl1K8higbZNG/BKpc1+iOipRl6eVWzkg2EegpNxEPVm8Kqn+9OfN28epk+fjri4ONSoUQNz5sxBZGRkgWVNJhOmTp2K3377DbGxsQgPD8e0adPQrl07qcz8+fMxf/58aZnxKlWqYMKECWjfvv1T1ZMpXcX9dzF16lSsXbsW58+fh1qtRsOGDTFt2jSEPy4h1auLgYQYwDkQkL5fUp7/39tCIixZBCeVL8Bzts9Tbhnc3y7tirDLaES0ghDmqAFgu4o9B8BoSgVlHkOo82LwnAxpiTqs/yUK1Wu8BL9Qd3ACB57jwfEAx/Pg741eLF3xG376ZSESExPxV2gYvho+Bo2aNQbupUeHaG0HiSJAhPnLfsPiP1ciNv4uXByd0LmBFyaMqQGVSgUCwWKx4JvvpmD12lVISIiHl6c33ni1N0aOGA2O46SmObqpoVDLrCMvZsK/s44jGRXhcToKAgfY16sA9xEfQO7jAwBw6NDhoYf/Rex4FFnJhZ48GRZwypQk0SKS7kQ8iWbLE+/jSVYT9fHxoQ0bNtCVK1fohx9+IJVKRSdOnJDKrF+/njZs2EAXL16kCxcu0P/+9z+Sy+V09uzZJ64nU7pK4u+ibdu29Ouvv9LZs2fp1KlT1KFDBwoICKCsrKzSalaxSYrNpLmDd9DdK2kPLVPUY7hs2TJSKpW0bNkyunbtGm3ZsoW8vb3po48+kspMnjyZXF1dpZkyq1evJnt7e5o1a9Yj6/vP+P20Ye4p0p04QRnbtxdrEOvzis12YZhHEE0W0p1OJFNi9hO9PjIykoYNGyb9bLFYyMfHh6ZOnVpgeW9vb5o7d67Nth49elDv3r0f+XucnZ3p52d4ee0XTWn8XSQkJBAA2rNnT/FUuhQl3MiguYN3UMKNjIeWKeoxHDZsGLVo0cJm28iRI6lRo0bSzx07dqR33nnHpkxhzr+tc07Rug930fFN10ivezGmyj6tonx+v5ip1ZgXGifjoanmBtFoQc65ZBjvZIHM4uNfiCdbTdRgMEClUtlsU6vVeVb5tGWxWLBy5UrodDprtkqm3CuNvwsASE+3BoW6uDx7cUuWe+cYLyv4lsSTHMOGDRvi+PHjOHLkCADg6tWr2LhxIzrkuSXSsGFD7NixAxcvXgQA/Pfff9i/f/9jb2k2e7cK3Op649rG6/h3/AFsnXUSZ3bfhi7dgKxUPRJuZIDEchUy+Wwphc5QkbCRD6a0mdP1lHMplbLPJ1P2+WTSX0kl0SIWWDY2NpYA0MGDB222jx49miIjIwt8TZ06dUgul5NcLqe6devS7NmzSa1Wk0KhsCl3+vRpsrOzu5eMiSeZTEbVq1enTZs22ZT74YcfqFq1aqTVakmr1VL9+vVp48aNT3EEmEeZO3cuBQYGklKppMjISIqKispX5quvviIAJJPJyNfXl3x9fUkmkxHP88RxnM3rvvzyS/Lx8ZFyYtjZ2dG8efOoX79+xHEcAaDg4GCKjIwkb29vAkDr1q0ji8VCHTt2tPlW/yy5dT6F5g7eQanxugKff5Jzi4ho1qxZJJfLSSaTEQAaMmSIzfMWi4XGjh0rJVjjOI6mTJlS6Hpnperp1LYbtOnro/Tn+7to2Xs7afl7O2n1sJ20c+HpQu/nRcBGPhimCAQHJVShTlCHu0Ad7gK5jz30MSkwxmY99b5XrVqF06dPo2rVqrBYLDh27Bg+/PBDvPHGG+AfWNMhPDwcb775JlxcXNCzZ084ODiga9eu6N69O06ePCmV8/Pzw9dff43jx4/j2LFjaNGiBbp27Ypz5849dX0ZW6tWrcLIkSMxceJEnDhxAjVq1EDbtm2RkJBgU+aLL74AAMjlcsTGxuLOnTsQRRGVKlUCAPj6+kqvW7RoEbKzs9GpUyeoVCrodDoMGzYMS5YsQdu2baFUKtG+fXscO3YMoaGhAIDXX38dPj4+OHHiBFauXFn6B6IY5I58CLLi+9jZvXs3pkyZgh9++AEnTpzA2rVrsWHDBnz55ZdSmT/++APLli3D8uXLceLECfz222/49ttv8dtvhcsdYuekRI1WAWg39iU0H/sSZBzgLbeO3sjVbM7GEyuFzlCRsJEPprwwJmZT9plEEk33g1MNBgMJgkDr1q2zKduvXz/q0qVLvn3kvYednZFBl/bvJy8XF2pQsSJVdHOja2/0ootNmlL26TNEZBsH0LJlSxo0aBCLDylDgYGBpNVqpVGPQ4cO5YtBiIyMpPDw8AIzfTZp0oS8vb3pzTffJB8fH2rTpg3JZAJxXP6yAKhOnVoUERFBGRkZZGdnJ42EaLVasrOzI3t7e7p9+3YZHpEnd+VkAs0dvIN06QUHbhb13CIiaty4MY0aNcpm25IlS0itVpPFYj1v/fz88sXWfPnllxQeHv7YOudkGWn379G05dtjtHXeKVo/9QitHmYd+Yi9mPrY179o2MgHwxQDuZsaqkouyDmXDEuWEcDjVxMlIphTUpB9/DgSVqzA8WPHUPPKFVxp3wHXGzSEacC7qGsy4dTly2jp4gLezg7mhASY7i2klTcOQBRFGAwGFh9SSubNm4egoCCoVCrUq1cPkyZNwo0bN9C/f39p1KN9+/Zo3LgxDhw4gEmTJiE4OBhHjhzBhQsXpP24urpK/9+3bx/i4uKwYsUKGI1GHD58GOAsILLmyqoQLIdCcb8Ox4+fhJ2dHfr27QudTiflSjCZTNDr9cjJyUFQUBCqVauGY8eOldqxKQ7SyIe84I+dx67UW4Ds7Ox8I4iCIACw5tp4VJncRenyIpGQFp+NxJuZSLyZiV2LziHtaDx4lQzGpBxQpgnV+lRC928awyfMqXANZwpW4l2hImIjH0x5pL+SStnnksiYoKOVK1eSUqmkn2fNoqO/L6F+zZqRo0pFR7p2o/OR9aiLgwO96+JCu0NCCQB93agx/dzrTTo+YwZt+eEH8vf1JaVSSampqWRKSaHo8Er0rosLbV/9J3Xu3JmCg4Np0KBBxHEcTZ069ZHxIYIgkKOjI23YsKGMjszzYeXKlSSTycjV1ZXkcjm5u7sTz/M2MQi5My+aNm1KXl5epNVqycPDo8ARjIIeCoWCAJCHh0AASC6XUefO7W3K8DxHnp6e0s+5Ix9OTk7k7OxMrq6uVKtWLVq/fj1dvny5jI9a0Zw/dIfmDt5BJqP5oWVyz63FixdTdHQ0DRo0iJycnCguLo6IiPr27Uvjxo2Tyk+cOJG0Wi2tWLGCrl69Slu3bqWQkBB67bXXpDL9+/cnX19faart2rVryc3NTVqULlfK3Sxa/fFe+mPYTlo1bCf9Mcwa1/HjkB307/SjlJZQcKwKcx+basswJcSYoKPMqGv0WUgt8lEoSc5xVE2lojWNGtHljh3p7pdfUeNq1ahPt+5068oVAkDz5s2zWaArIiKCatasSaLJRMnffUbR4ZWoh6MjBXq5kUIuI4VcJn0QVQzyo/d6dSSVSmkT+PjSSy/Rn3/+SceOHaNx48aRm5sbnTt37n49jUb64osvKDg4mJRKZYGBq3n35+fnRwBoxIgRBbe7EPt7lgNhQ0JCiOd5Kb/E22+/LXUA8gZA9uvXTyrr6OhIixYtsuk8yGQyEgQhX8dDEARSqVQEgFq0cCxUZ+X+yrH5H7/++mvZHawndG5fLM0dvOOhwdy5HrpSL1G+xe8etShdrsIuSnf7fAqtG76TVt7reOQ+1o3aS+vf30l7lsQUy3F4nrHOB8OUIEt2Nl1u34FiajehC01fsT6av0YXmrxCF5r0pMtdB9CtUf+j5J27HnoPu1PThnStRU2KDg+nu538yPI/R+sqpPceOZ9o6fZH9jSnnZIcFPe/BX/66acFJl9q2bIlNWzYkJycnKRvy4Ig0BdffGGTwGr8+PFUrVo1UiqVNh+WHMcRz/M0cODAAtvctGlTAkBdunR57hKlGQwGAkAqlUqK7Vi/fr30QZ/3/Rs9ejS5urpKcRi5xzH3WAKgWbNm5esscBwndfDG/68CBQW52zzv4uJyrxwoNDSU/P39ydvbm9Rqdb79KJVK+vHHH8vugD2h07tu0Q/v7SzrajzSuX23ac/SGDq++Tqd3XubTu24Sf98fYT+fH8X3TibVNbVK/dKrPPxuG82d+/epT59+pCnpydpNBqqVasW/fnnnyVWeYYpa+bMTErfupWSlywl3YkTlL5pE92dMo0ud32bLjR7herWqUPDhw+XypvSU8nbXk0fubvR5XqVSLfuB6LsFJr7/TQKDPC3fvi9VJuidm2ilb8uIDkP8tBw5K5VUER4KDk5OdFXX31Fjo73vz2HhoZSQECA9OGU+yGY9+Hp6Uk8z5OdnR198cUX5O7uTjKZjOzs7GyG93mel87rKVOm0EsvvUQajUb6cO7Xr5/UlmcxELagabNz5swhANSzZ0+pY5d7fDmOIycnJ1KpVOTn50d16tSRbsc4OTnRypUrHzl6kVs272Ps2GCbgNPcY5/7GDx4MMXExEgjJbmPKlWqkEajoapVq5JKpaLFixeX9eEsklPbb9KC93eVdTVsmAxm2rMkmjZ+fog2TjxIGyceoo0TD9G6kXukkY8NX0XRzZjksq7qM6HEOh+P+2bTunVrqlu3LkVFRdGVK1foyy+/JJ7nbb4dFWflGaa80l+5QheavkpzmrUmpVxOixYspKNzJtPr7k7kwPN0dlBHsmSkUN++falr165SSukVK1ZQq1atyMHBgcLCwsjXw5mCnGXEA7TmNRU5q60fVPb29lSzZk2pE5H7AdW7d286d+6ctM3e3p4A0KeffkpdunQhFxcX6du6RqOhFi1akEwmo+bNm0sdjNzzulGjRjR//nwKCAggOzs7srOzI61WK6X27t27NwUGBhbYfrPZTCtWrCCFQmFzO6gsPSx1d+5MldxjExkZSW5ubjYjGtOnT6effvpJuqWi0WjydRoK8+DAkZ1GuNcxAXXrpiVBAMnl98t4eHhQYGAg+fj40JYtWwgABQUFUfPmzUkmk9HChQvp/fffp/r165f1IS2SE1tv0I8jdpd1NWzcuZxG/76/ixYN3UGLh+6gpe/tpPmDd9CRf67QtdOJD52ZwxSsVG+75P1mY2dnR7///rvN8y4uLvTTTz8Ven+s88E8LzL37qWrbwy2xocoNSTnOKrhoKFdb9Uk0++DSdw3i5o1bUpubm7SdNzdu3dTpUqVpA+i5s2b0/EDO62xB+9oyM3OmiTJxcWFBEHIF2NQoUIFioqKojfeeIM4jpM+ICdOnCgFroaGhkrlc5MznTt3TtrPlClTSBAEUiqVpFQqKTg4mDp27CjdAti1axdt3br1mQuELSh1d24SrwdHPnKDQzmOs4lB4HleOg5536fCPkL9gx9bxt7evsARk9znjEYj/fDDD+Tj41OGR7Pojm++Tj+NLF9p4UWLSFF/X6F/Jh2mVcN20vr3d9I/kw4//oVMgUplqm1BU/waNmyIVatWISUlBaIoYuXKldDr9WjevPlD92MwGJCRkWHzYJjngX2TJqiwYgE+3f0PTg9piIR3KuHItFfQuFkkKMeAnK2bsb6FFqkpyWhV1RMA0KxZM8TExOCVV14BAEyZMgVeppsAAFOl7kjOtoDjOHzzzTcYOXIkAgMDpSmDMpkMqampaNWqFT755BPrqp73phv+9NNPePvttyGKIm7evJmvrnv27IHFYgEArFy5EhzHYfjw4fD390dYWBhOnToFxb05oa1atcLw4cPx9ttvF5go7dSpU4iKisLQoUPRv39/REdHl8DRLZqHpe5u1KiR9HNOTg4iIiKwYMECyOVyAAARITExEZs3b0aPHj0AAJUrV0ZYWJiUrruw3NzckG3Rg+c4yHkB/q5h4DlBWgFVJpPh4vnL+PHHHyGXyzF27FgEBARIz3t6euLatWuQy+W4ePEiAgMDn+qYlDbRQuD58rXaK8dziOwSjIptAyHngOBXK6L9+LplXa0XQ1F7No/6ZpOamkpt2rSRhiodHBxoy5Ytj9zfxIkTC+zhs5EP5rl35xTdXjrCOprwVj0y/dyPKD6aiIiGDh1qHe04eJAM2ToSeI5+6WKNAXDQqCgiIoK6detGjo6OUiCjIAjUpUsXKdZAqVRKIx/z5s2j0aNHS2nbCzrn8j4WLVpEHh4e9N9//0mLmTk4OJCXlxfdvn2bRFGkMWPGUERExCObmJsoraw9LHX3oEGDpFsugiBIUzydnJwKHN1oZW9Pg+8FhzrJZFRfpaIqeYJOH3xw4KQRlIeNZgAgldyOhnWYRsM6TiM/70Bq0KABBQcHk0KhIFdXV+J5nj777DO6dOkSLVu2jDQaDS1durSMjuaTifrnKv06Zl9ZV6NA2ZkGWjNmL/39xSEyZJvKujrPrBK97WIwGOjSpUsFTvEbPnw4RUZG0vbt2+nUqVP0+eefk6OjI50+/fD893q9ntLT06XHrVu3WOeDeWFIH4rLp5NhemfK/qwtmZcOopE96xMAWvdFLxI3/I/qVnCjnjWt+R/UwWrS1tJKH1y5AaEymYzMaXp687Ve1KpFS4qoVNnm9kHuvy+//DJxHEe+vr4FfiAOGDCANCprICrPCcRztmV4TqAfP95BHk6+1KlBX/pt/AFaNHof7fw9Ol/7Xn75ZZupkWXlcZ2PXr162eT5yL0F5ebmRj/99BO5uLhQQEAAeclk5C2TUZBcbntM7h3HefPmkVqlljodAIgHJ90ek8vl1CD8ZZo7eAfN/nUpGQwG+vR/n5GfdyDJBQU523tQlxZv2EwVJSL6559/qGrVqqRUKqlSpUrP5GyXQ39dpsXj95d1NfIRRZGy0vQUfSCW1gzfSef2xZZ1lZ5ZRel8FDkxvUKhkNYbqFOnDo4ePYpZs2ZhzJgxmDt3Ls6ePYsqVaoAAGrUqIF9+/Zh3rx5WLBgQYH7UyqVUCqVRa0GwzwX3NzcIAgC4tWhUHz4AejYYpiO7EH8tTg4qeTYsvkI2qkJg1tVwZBFewEAfipP6LR66FQ6iHoRjr6OyL6UDRIJN6YehMN14Mjly7iRFguC9bZLRddAZBqzUa9FI+zdtxceHh5ISkrCiBEjMGPGDKk+SqUSzbzewR/cWni5uOL7SQvwwYS3kJqWDDdXT4QHV0Hz+q3x47ZPIVPy+GDYR1Ar7fHf9luYsXAqhMB3ERAQgMzMTCxfvhy7d+/Gli1byuLQ2pCOc3y8zfaUlBQA1tsyM2bMwKRp02DJyIBIBE4Q4N2pO6Lqt4LRJQDJKldUfcmMqLV3IAiAnUYGXbYZvIwDJxJ4joO3LgXD6r6J7/f/Kt3yEkEQzWYA1tvVId4vAQCCs6thy4JoBJvbYFyX5gAA71BHdBtZO9/tiU6dOqFTp04leYhKHInl77YLAOxffgGJh+/CQgCnFOBZwaGsq/RCeOr06rkpoLOzs607LGQaW4ZhHkgpLVOAqz8IsuFLsDvehDbduuPn4zfQ/VYyNnpo4BxoXUb9Usx1uGV5oG4t673p+LvWD1SLaMGbO8fjWGYMbmXehUk0wyxa4ziSclLRvFpFOLsQsrIyER8fD4PBgJkzZ9rUx93eHxlJepgtJmicZJg8fzRS05MxY+YMZOrScODYTsxbOg2Va4Ti6InDaNylCuKvpkOQ81C5WdCvXz+Eh4ejZcuWOHr0KLZs2YLWrVuX3gF9iIel7j548CA4jsPff/8NrVaLBnN+gUP7ruB4AYJKDSM4bBv3EXiPMLh1/AhpbpUBABZw8O5bB7xaBoeGYVCr1AAAk16PHD4TGrkK3s4eWPbBPBybthm/DpsJgRdQu0I1vNm4G+y11pgSuUqAb5gTPAK16D+1EXqMqlMuP6CLg2gh8ELZr+ghioT/tt/EjoVncHb3LaQl5sBCQN3B1dB1aiO4+tqXdRVfCEUa+Rg/fjzat29f4DebSpUqITQ0FIMHD8a3334LV1dX/PXXX9i2bRv+/fffkqo/wzzzRo4cif79++Oll15CZGQkZs6cCZ1Oh1bvt8JN82VsXbgDZCZE1IjAwImDMX3KdDRt2BR79uwBAFA2QWYvg1lnRtTRKGm/HMchpGlXXN7zF1LNevxx4RzEsyJEswXgOABk/XbOARxx0Gpc8Grj9/F31M/Qm3Qwmcy4di0as6f/iA5tW2PFihWoUqUKZs+eDbVajZS7Ovw57RhMRhHdR9bGkArLyugIFk5Bxzk7Oxs1a9aEVqvFsGHDkJ2TA+fKVeHm7ITq1avjyJoV8PPzg0nrDf3t/yAcugYnJydUjohAwvZ4wEBI23cZlatUxbXLF8FXrolVsxdiwNCBAIDx66YhISEBXl5ekCvk6D38LbQf2bCMj0TZEEVCdoYRaQnZsJjufSHlcv/hbH/O0//ibH64/7y0/d7/rT9a/71xLhmGbDN8Qp3g5m9vs5Ju3JU03PnnKnJEQsbZJJgJEDjgzK7b8Ah0gFwhFHvbmfw4yh0bLIQBAwZgx44duHv3LhwdHVG9enWMHTtW+mZz6dIljBs3Dvv370dWVhZCQ0MxatQo9O3bt9AVysjIgKOjI9LT06VFlRjmeTd37lxMnz4dcXFxqFmzJmbPno3IyEi8uqoHDn12CBE1qmHbn9sAACNGjMAPP/wA872h/ICAAOzcsxMT5kzAitkrQGaCwk4Oo86U7/fY+3hi5OLPceXqdfwz9Xdk3UmEaDKD5wVw4KBW2MPHtQKUMhXO3DhUYF1/Wvgz2jbtjs0Lz8LeWYmOw6rDwVVdcgenGBV0nK9fv47+/fsjKCgI2T7+ULm4IXHHZpw9exY///wzvv32W+iyc6C0d0D/itlwUBAWHDPhu07O0Pk2wJeb7yD96hkQiQgKCkKvXr2g0+nQrVs3BAYG4s6dO5g4cSJOnTqF6OhouLu7l/VhKBMH117Gya35Z1qVNLlSgCDn4aA3Q1DwcAx3RnKSHmKqAdCbpeF/GQfIPTXoMK6uTWeFKbyifH4XqfNRGljng2HuM1lMmLTrc6RGxyKkQQ20DW6Lis4VIeOtg5arVq1C//79MXLqSCSo7+LA0v24evImGk2ORP20IPy96hIEB1806NwbR2oF4OaNGGhvXkWD0CDUk/P457dfcfzSFXh88xta6+zxafNQjBzzITZsW4f53/2Gm/vN8A13hl8lJ1w+kAZT9v1voQERLmgzsCqU6iKHjpU7uZ2S23fj4BJeGf/+vBD16tUDADRv3hxuPn5o2LYGRl77Cscqj8WiNTuwfucRJKdnwV3DoVWPPvh+xmw4OTkBAN544w3s3bsXycnJcHd3R+PGjTF58mSEhISUYSvLllFvRsKNTACA7IGVbaVPIcqNUgLy/uf+8/c255Yj63To+9shxdp4VnBAemIObp5LwdF/r8FLxkHtbQeLwQx9ikH6Fbl/0RwAOQfU/aAWW7H2CbHOB8M8R0QS8dOJH3Hi6AGYLCbwnAAnpRPkSgVIFLHv34P4b3s0cjL1CKsShl8X/IoG9a25d5o3bw4vN1d8+MarOLJpF2L0cizbux5Z8fGAWgOH2nUhf28UBDcPnGlUBe4Kue0wdx6//vormtfphA3zTsMnzAldP6xZLu7hFyevXacAAL9UDQKQ50MRgN2GD/Dyjb+BV3+7d1+Ag+nOGcj3fwN8cBJwCS71+jKFkxqnQ+zFNFSMcIYpNgt8iBPSE3Kg15kgyHgIch7x1zLg4KZCcE33h54DzKOxzgfDPIeMFiPOJp1FTEoMknOSkZWdCV7g4evoh0a+jVDBocIjL5qXjx7GsR9WgVPJoNQ64CQsOBwUgOiQKhhL6Rjerk2h6kFEz+3Fucr+s0g2mQt8Lm5Ps4JfJFMBI2MAjUsJ1owpLqLRAn10MlSVXcErWXxHcWKdD4ZhChR3+SLObt8G8IA53YCc2DToMzLQ6PU+cPcLgjLMGfwLHHBnIUKG2SL9nHdIHkYdtDkJ4O3cbIdEZCpAoSnNajJPiSwiDNczALM18JUIUAY6gH8ObiGWpaJ8frMjzTAvEK/QivAKrVjgcyQSDFfSQBYCJ+OhDHQAJ3++bqs8jsBxcJY/5LIodwTsHEu3QkyxMacbYLqVCdwLJn1w8M6SZWSdj1LEjjTDMACs61yowpwBAGSywHAjHWS2fsNX+NhBcGDJAJlnl6CRwXRvSq7cxx4gwJSYDTKLgEiQuajKuoovFNb5YBgmH04uQBV6ryNCBNPtLBjv6KCuxOIamGcTJxegruIKMoswxekAnoMywAFkEaE/n5Jndg1TGl6sMVWGYYqM4zgo/LWAhWUqZp59nIyHwk8LhY89ODkPw7V0qGu4g2O5PUoVO9oMwzwWmSzAczatlmEMNzIgOCif29lb5Rm77cIwzGNxcgG8SoD+Qoo1Uu/ebA+LzgTeTg6FN4sJYZ4dlgwDDDcyofC1Z7EeZYR1PhiGKRRlUMEzPUgkmO5kwXgrE6oIV/Ytkil3RL0ZxpuZING6lpFgJ4e6KvtbLUus88EwzFPheA4KPy1ENzX0MSngBM46OiJwkDmrIDgqrdsYphSJerM1lwcAXiVAGeIIjt06LDdY54NhmGLBq2RQR7hKP5NZhDlVD8PVNEAkkEiQe2gge0YWoWOeXaZ4HcyJOVBVYaMb5RXrfDAMUyI4GQ+5uwZyd2v2TxIJ+vMprPPBlBhRb4b+QioUvvZQV3Ur6+owj8A6HwzDlApzUg7kXnZlXQ3mOaaPSYGaLQz3TGA3wBiGKRWi3nx/sRSGKQGcWsY6Hs8I1vlgGKZUKPy1MCflwHA9vayrwjynOM46/Zsp/1jng2GYUsFx1rVjZC4q5JxLhvF2ZllXiXnOKCs6w3A5DaLB8vjCTJlinQ+GYUqV4KCEuooreHs5cs6nlHV1mOcIx3FQV3ODPia5rKvCPAYLOGUYplTknE0CJ+eltcyJCHI3NvOFKV4cz4FXy2C4mQGFnxYcz2JAyiPW+WAYpnTIeajC2aq4TMlThbvAkmmE/lIqYCEo/LQQHBRlXS0mD3bbhWGY0iESiNi65UzpELQKqMNdoKrsAnOaHjnnkkFsZeZyg418MAxTKpQVHJFzOhGqcBfwKnbpYUoHx3FQBjiAzCIMl9NABAj2cij8tGVdtRcaG/lgGKZU8CoZ1NXdob+QwmYjMKWOk1lv+6kruQAcB1NidllX6YXGOh8Mw5Qa62wEd+gvpsKSYSjr6jAvKN5ODjHbXNbVeKGxsU+GYUoVx3PQVHOD/lIqLDozFN4s5TpTvMhkgai3gESyxhqZRIDnwMk4GG9kQnBSQhnoUNbVfKGxzgfDMGVCFeYMU0I2cs4lQ+aqYuu+MDaICGK2GWK2CWQSIeaYAQvlLZD/Rbmp1QUOvEoGTuDudTp4gAikt0BdzY1Nvy0HWOeDYZgyI/fQQO6hgTk5B9lnkqDwt4fMSVXW1WJKGVkIxtuZEPVmm+V/eI0cvJ0cvEoGuYfG2olgngus88EwTJmTuaohc1XDcDUNZBQh99CUdZWYpyAaLTAn5QAWgtzLzppcrgCGmxkQs83geA4KP3vwGnkp15QpK6zzwTBMuaEMdkJOTDIEBwWbjvsMsWQaYYzNklYt5uU8ZG4aQOBguJlhjbkAoApxBATeOsqRYYQiwAFCAEv+9SJiZzfDMOWKqpILcs4kQVPdvayrwjwGWQj6mGTwDgqowp0LXM5eCHGylhUJhitpAAFyHzsIASzg80XGOh8Mw5QrHMc9dJieKV/0MclQVXIpVCwGx1tXNWYYgOX5YBimnLFkGiHYs6H48s6SZQSvVbAgUOaJsJEPhmHKDBEBZoKoN0PUm2FJ0YNMIlRVXMu6asxjmO7ooKzAbp0wT4Z1PhiGKVUkEgxX00Fm0ZqWQcaDV8nAqwQoQ53ACeybdHlnvJMFTiWAkwtlXRXmGcU6HwzDlBrDjQyI2SYoAx3YtMpnlOFmBjiBh5IFjDJPgXU+GIYpFblruagrs1sqzyrD9XTwahnkniwbLfN02PgmwzClwpJpKusqME/JnJgDmTtLAMc8Pdb5YBimVCh87SFzUiL7dCIsWcayrg7zBARHJTK23yjrajDPAXbbhWGYUiM4KqGu5gbjzUyY7ujuLw4m46G6l4yKKb+UYU7gNTK2GCDz1Fjng2GYUsVxnM1y5sa7OhSQGPOZRRYR5qQcWNKNIKMFumPxcGgdCN5OhpwzSRAclFCFOz+T6eM5joPCTwv4AabEbORcSIE63KWsq8U8g569v36GYZ4rluQcqKu6lXU1nhgRwXQ7CxadNaaF4znIPNTWacM8B1WEK8RsE0SdCcpgJ5DJAlOcDmSw4MFF4QU7OeSeD1+IrTyRu2vAq2TIiUkGOA7KAC2bwcQUGut8MAxTpuT+Whiup0MZ5FjWVSkSMoswXEkDWQgKfy0U/toCy3E8B8FeUaisrZYso3UhNrMobeOVAmRuavB28gLXTilLglYBdWXXe7lb0iDYK9itGKZQWOeDYZgyJXNUQtSZYLiaDmVw+e+AWHQmGG9kgJPxUAY7FesoRUGdFFFvhjlZD1NslhQio6zgCF5ZfhJ8cTwHVagzcs6nWFckZiMgzGOwzgfDMGVO4WMPc6oeOTHJ5TYPiEVngvF6Bnh7OVSVXUptFIJXyaDwtZd+JgvBcD0dZLSA18ih8NOCE8rHiIgq3BnZJxKgqeUBji8fdWLKJ9b5YBimXJA5qwAOyIlOLtUP98IQ9WYYrqZDU63sY1M4gZNmBonZJhgup4II4DhA5q4BbycHQICFwKllpXocOY6Duqobck4nQlPTo9R+L/PsYZ0PhmHKDZmTyhrEeDoJCn8tZC6qsq4SRIMZ+gspUFdzL+uq5MNr5FDdm21CIsGclAPT3ax7T3IgveX+dGYAnEoGmZsagl3J3RYxXE2DqhKbAcM8Gut8MAxTrvAqGTQ13GG8q0NOTLI1tiLIsdRngOSN7VBXcy/3txE4noPc49HZR8Ucs7WDEptlXVGYAE7OQ+GvBa94+hgS/eU0aRYMwzwK+wthGKZcUnjbAd52IJMI/aVUa1KrEl5ThERCzrlkcHIevFpW7m7/PC1eLcs3K0c0WmC8lQkyWCBzefLEYUQE4+1MqEKdiqGmzPOOdT4YhinXODkPdYQrcs4mlWjnw3grE+bkHHAKAeoX6LYBrxCkGBJTYjayTydC5qaG3EMDTla40SZLhhGGa+mwr+9dgjVlnidF6nzMnz8f8+fPx/Xr1wEAVapUwYQJE9C+fXtcv34dFSpUKPB1f/zxB1599dWnrizDMC8mMdsEPOaDMCc6WZr1QWS9DUFmEWS0QF3NDZxQ8OuJCPpzyZD72EPzkFwdLwq5uwYyNzWMtzJhuJ4BiPfiRfLEjYDj7v987/+c2nqrjGEKq0idDz8/P3z99dcICwsDEeG3335D165dcfLkSVSqVAl37961Kf/jjz9i+vTpaN++fbFWmmGYF4vhegZUFZ0f+jyJBDHbBGWoEwRHpc2tEjKLyDmdBFWEa4G5MQyX06AMcQKvZgPBwL309wEOjy/IME+BI6IHM/wWiYuLC6ZPn44BAwbke65WrVqoXbs2fvnll0LvLyMjA46OjkhPT4eDAzsBGIa5l9vicipIJHACb52x4fxAJ4MI5vhsWNINUtpyZQVH8ArBmoHzShrILEJwUELuYye9Nud8ygt1m4VhSkpRPr+fuKtvsViwevVq6HQ6NGjQIN/zx48fx6lTpzBv3rwn/RUMwzAA7uW2yDulNDkHhoup1k4GAXJPDWTO1mDJ3IBJsojIPpkIdTU38EoBqjDryIk53QD9+RTwGjmUgQ6QOSthuJnBvu0zTCkqcufjzJkzaNCgAfR6Pezt7bFu3TpERETkK/fLL7+gcuXKaNiw4SP3ZzAYYDAYpJ8zMjKKWiWGYV4gHM9B7q6B3P3+tFLjnSzk3E0Gr5FBEeBgjfcwWKyzVh641SJzVELmqIT+cipEgwVyTzuYknKQE50MQauA3M/+uZrhwjDlUZEnzoeHh+PUqVOIiorC0KFD0b9/f0RHR9uUycnJwfLlywu8FfOgqVOnwtHRUXr4+/sXtUoMw7zgFD72UEe4Qu6hgeFSKnIupMCUkA119YdnJFX4a2G4kgYAkLupoY5wBa+VI+vgHWTsummzuBvDMMXrqWM+WrVqhZCQECxcuFDatmTJEgwYMACxsbFwd390BHRBIx/+/v4s5oNhmBJnTtXDFJ9tnbQBWONJnJQQnJSFnmbKMIxVqcR85BJF0abzAFhvuXTp0uWxHQ8AUCqVUCqVT1sNhmGYIpM5q6xryjAMU6qK1PkYP3482rdvj4CAAGRmZmL58uXYvXs3tmzZIpW5fPky9u7di40bNxZ7ZRmGYRiGefYVqfORkJCAfv364e7du3B0dET16tWxZcsWtG7dWiqzaNEi+Pn5oU2bNsVeWYZhGIZhnn1PHfNR3FieD4ZhGIZ59hTl85tFVDEMwzAMU6pY54NhGIZhmFLFOh8MwzAMw5Qq1vlgGIZhGKZUsc4HwzAMwzClinU+GIZhGIYpVazzwTAMwzBMqWKdD4ZhGIZhShXrfDAMwzAMU6pY54NhGIZhmFLFOh8MwzAMw5SqIi0sVxpyl5rJyMgo45owDMMwDFNYuZ/bhVkyrtx1PjIzMwEA/v7+ZVwThmEYhmGKKjMzE46Ojo8sU+5WtRVFEXfu3IFWqwXHccW+/4yMDPj7++PWrVvP5aq5z3v7gOe/jax9zzbWvmcba9+TIyJkZmbCx8cHPP/oqI5yN/LB8zz8/PxK/Pc4ODg8l39YuZ739gHPfxtZ+55trH3PNta+J/O4EY9cLOCUYRiGYZhSxTofDMMwDMOUqheu86FUKjFx4kQolcqyrkqJeN7bBzz/bWTte7ax9j3bWPtKR7kLOGUYhmEY5vn2wo18MAzDMAxTtljng2EYhmGYUsU6HwzDMAzDlCrW+WAYhmEYplQ9l52PEydOoHXr1nBycoKrqysGDRqErKwsmzIffPAB6tSpA6VSiZo1axZqv82bNwfHcTaPIUOGlEALHq2k2qfX6zFs2DC4urrC3t4ePXv2RHx8fAm04NEK076bN2+iY8eO0Gg08PDwwOjRo2E2mx+536CgoHzv39dff12STSlQSbUvJSUFvXv3hoODA5ycnDBgwIB8+y0NFy9eRNeuXeHm5gYHBwc0btwYu3btsimzY8cONGzYEFqtFl5eXhg7duxj21dezr+Sal95Of8K076jR4+iZcuWcHJygrOzM9q2bYv//vvvkft9lt6/J2lfeXn/gMe3cfHixfnei9xHQkLCQ/dbrNdQes7ExsaSs7MzDRkyhM6fP09Hjhyhhg0bUs+ePW3Kvf/++zR37lzq27cv1ahRo1D7btasGQ0cOJDu3r0rPdLT00ugFQ9Xku0bMmQI+fv7044dO+jYsWNUv359atiwYQm04uEK0z6z2UxVq1alVq1a0cmTJ2njxo3k5uZG48ePf+S+AwMDadKkSTbvX1ZWVkk3yUZJtq9du3ZUo0YNOnz4MO3bt49CQ0OpV69eJd2kfMLCwqhDhw7033//0cWLF+m9994jjUZDd+/eJSKiU6dOkUKhoC+++IIuXbpEu3fvpkqVKtHHH3/8yP2Wh/OPqOTaVx7OP6LHty8zM5NcXFzorbfeovPnz9PZs2epZ8+e5OnpSUaj8aH7fVbevydtX3l5/4ge38bs7Gyb9+Hu3bvUtm1batas2SP3W5zX0Oeu87Fw4ULy8PAgi8UibTt9+jQBoEuXLuUrP3HixCJ1PkaMGFFMNX0yJdW+tLQ0ksvltHr1amlbTEwMAaBDhw4VS90LozDt27hxI/E8T3FxcVKZ+fPnk4ODAxkMhofuOzAwkGbMmFFidS+MkmpfdHQ0AaCjR49K2zZt2kQcx1FsbGwJtSa/xMREAkB79+6VtmVkZBAA2rZtGxERjR8/nl566SWb161fv55UKhVlZGQ8dN/l4fwrqfaVl/OvMO07evQoAaCbN29KZR51Dcr1rLx/T9K+8vL+ERWujQ9KSEgguVxOv//++yP3XZzX0OfutovBYIBCobBZ1EatVgMA9u/f/9T7X7ZsGdzc3FC1alWMHz8e2dnZT73Poiip9h0/fhwmkwmtWrWStlWqVAkBAQE4dOjQk1e4iArTvkOHDqFatWrw9PSUyrRt2xYZGRk4d+7cI/f/9ddfw9XVFbVq1cL06dMfOxRe3EqqfYcOHYKTkxNeeuklaVurVq3A8zyioqJKoikFcnV1RXh4OH7//XfodDqYzWYsXLgQHh4eqFOnDgDrMVCpVDavU6vV0Ov1OH78+CP3X9bnX0m1r7ycf4VpX3h4OFxdXfHLL7/AaDQiJycHv/zyCypXroygoKBH7v9ZeP+epH3l5f0DCtfGB/3+++/QaDR45ZVXHrv/YruGFksXphw5e/YsyWQy+uabb8hgMFBKSgr17NmTANCUKVPylS/KyMfChQtp8+bNdPr0aVq6dCn5+vpS9+7di7kFj1ZS7Vu2bBkpFIp82+vWrUtjxowpjqoXSmHaN3DgQGrTpo3N63Q6HQGgjRs3PnTf3333He3atYv+++8/mj9/Pjk5OdFHH31Uou15UEm1b/LkyVSxYsV8293d3emHH34o/oY8wq1bt6hOnTrEcRwJgkDe3t504sQJ6fktW7YQz/O0fPlyMpvNdPv2bWrSpAkBoOXLlz90v+Xh/CMqmfaVl/OP6PHtIyI6c+YMhYSEEM/zxPM8hYeH0/Xr1x+532fl/SMqevvK0/tHVLg25lW5cmUaOnToY/dbnNfQZ2bkY9y4cQ8NkMl9nD9/HlWqVMFvv/2G7777DhqNBl5eXqhQoQI8PT0fu8Tv4wwaNAht27ZFtWrV0Lt3b/z+++9Yt24drly58ly0rySVh/aNHDkSzZs3R/Xq1TFkyBB89913mDNnDgwGw3PRvpJU2PYREYYNGwYPDw/s27cPR44cQbdu3dC5c2fcvXsXANCmTRtMnz4dQ4YMgVKpRMWKFdGhQwcAeOQxKA/nX0m2ryQVZ/tycnIwYMAANGrUCIcPH8aBAwdQtWpVdOzYETk5OQ+tw7Py/j1p+0pacbYxr0OHDiEmJgYDBgx4bB2K9Rr6RF2WMpCQkEAxMTGPfDx4PzwuLo4yMzMpKyuLeJ6nP/74I99+izLy8aCsrCwCQJs3b36i1+dV1u3bsWMHAaDU1FSb7QEBAfT9998/TdOIqHjb99lnn+Vr09WrVwnAI3v3Dzp79iwBoPPnzz/z7fvll1/IycnJZpvJZCJBEGjt2rWl1r7t27cTz/P5AglDQ0Np6tSpNttEUaTY2FjKzs6WYlaOHDlS6DqVxflXUu0rL+dfYdr3888/54tbMhgMpNFoaMWKFYWuU3l9/56kfSX9/hV3G/N65513qGbNmk9Up6e5hsqK3l0pG+7u7nB3dy/Sa3LvmS9atAgqlQqtW7cu1jqdOnUKAODt7f3U+yrr9tWpUwdyuRw7duxAz549AQAXLlzAzZs30aBBgyfeb67ibF+DBg0wefJkJCQkwMPDAwCwbds2ODg4ICIiotD7P3XqFHiel/bxNMq6fQ0aNEBaWhqOHz8u3dfduXMnRFFEvXr19tSwIgAAA1xJREFUnrRZksK2L/ce/oPf8HmehyiKNts4joOPjw8AYMWKFfD390ft2rULXaeyOP9Kqn3l5fwrTPuys7PB8zw4jrN5nuO4fMfgUcrr+/ck7Svp9w8omb/RrKws/PHHH5g6deoT1emprqFP1N0p5+bMmUPHjx+nCxcu0Ny5c0mtVtOsWbNsyly6dIlOnjxJgwcPpooVK9LJkyfp5MmT0rfT27dvU3h4OEVFRRER0eXLl2nSpEl07NgxunbtGv39998UHBxMTZs2fS7aR2SdKhYQEEA7d+6kY8eOUYMGDahBgwal2jaix7cvdypqmzZt6NSpU7R582Zyd3e3mYoaFRVF4eHhdPv2bSIiOnjwIM2YMYNOnTpFV65coaVLl5K7uzv169fvuWgfkXWqba1atSgqKor2799PYWFhpT7VNjExkVxdXalHjx506tQpunDhAo0aNYrkcjmdOnVKKvfNN9/Q6dOn6ezZszRp0iSSy+W0bt066fnyev6VVPuIysf5V5j2xcTEkFKppKFDh1J0dDSdPXuW+vTpQ46OjnTnzp0C2/csvX9P0j6i8vH+FbaNuX7++WdSqVT5RmyISv4a+lx2Pvr27UsuLi6kUCioevXqBU4fatasGQHI97h27RoREV27do0A0K5du4iI6ObNm9S0aVNycXEhpVJJoaGhNHr06DKZp14S7SMiysnJoffee4+cnZ1Jo9FQ9+7dpXnhpakw7bt+/Tq1b9+e1Go1ubm50ccff0wmk0l6fteuXTbtPX78ONWrV48cHR1JpVJR5cqVacqUKaTX60urWZKSaB8RUXJyMvXq1Yvs7e3JwcGB3n77bcrMzCyNJtk4evQotWnThlxcXEir1VL9+vXzBcq+/PLL0ntRr169fM+X5/OvJNpHVH7Ov8K0b+vWrdSoUSNydHQkZ2dnatGihc2U0mf9/Stq+4jKz/tHVLg2EhE1aNCA3nzzzQL3UdLXUI6I6InGWxiGYRiGYZ5A+Q2vZxiGYRjmucQ6HwzDMAzDlCrW+WAYhmEYplSxzgfDMAzDMKWKdT4YhmEYhilVrPPBMAzDMEypYp0PhmEYhmFKFet8MAzDMAxTqljng2EYhmGYUsU6HwzDMAzDlCrW+WAYhmEYplSxzgfDMAzDMKXq/11uPe+0FRotAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"overused units\")\n",
    "maxPlot = 1.06\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > maxPlot:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(round(unitUse[u],2),unitGeom[u])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()\n",
    "print(\"underused units\")\n",
    "minPlot = 0.94\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < minPlot:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(round(unitUse[u],2),unitGeom[u])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fa912158-e8e9-46f3-8c3d-f6b17c26e62c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Note - for MA, above is second run-through after overuse, then underuse pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "0d4f1372-6044-4803-91d9-de4b95a40083",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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8KEk6ePCgqqqqLgg9ZWVlllX2Dx8+rLvuuuuCvhBgAABwYq6urhesf3buMySSLggQLi4uqq6ubvQ1/vKXv2jZsmVKTExUv3795Ovrq4SEBMsK9/UxmUwX/eyGaisqKpKbm5tSU1OtQo4ktWvXrtH12wsBBgCAZurUqZNOnDhh+bqwsFDp6elN/pyvvvpKXbt2lSTl5eXp6NGj6t27tyRp7969uvPOO3X//fdLkqqrq3X06FH16dPH8n5PT09VVVVZfWb//v21bt06VVRUNDgKU5+BAweqqqpKubm5uuGGG+ps07t3byUnJ1/Ql5bAQ7wAADTTTTfdpHfffVdffPGFDh48qEmTJl0wWtEYCxYs0I4dO/T999/rwQcfVMeOHTV27FhJUvfu3bV9+3bt27dPhw8f1qOPPqqcnByr919xxRVKTk7Wzz//rFOnTqm6ulrx8fEqLCzUhAkTdODAAR07dkzvvvuujhw50qiaevToodjYWE2cOFGbNm1Senq6UlJStHjxYm3ZskWS9MQTT2jr1q1aunSpjh07pldffbVFbh9JjMAAAJzdqaNOe52ZM2cqPT1dd9xxh/z9/bVw4cJmjcC88MILmjZtmo4dO6bIyEj97//+rzw9PSVJs2bN0k8//aSYmBj5+Pho6tSpGjt2rAoKCizvf/rppzVp0iT16dNHJSUlSk9P1xVXXKGdO3fqmWee0fDhw+Xm5qbIyEhdd911ja5rzZo1ev755/XUU08pKytLHTt21LBhw3THHXdIkoYNG6Y333xTc+fO1Zw5cxQdHa1Zs2Zp4cKFTf4eNJWLuTGbFxlQYWGh/P39VVBQID8/P0eXAzTNL2nSG8Olqbtr1qdobhvAIEpLS5Wenq6IiAh5e3vXHGwDK/Hu2rVLI0eOVF5engICAlrkms6gzt/v/9PYn9+MwAAAnFNAeE2YYC8k1IEAA7RhWfklyiuumcnQwddTXQIuPmsBaFEB4QQK1IkAA7RRWfklin5pt0oqamYumDzc9NlTwwkxQAsaMWLEBdOw0TjMQgLaqLzicpVUVCnxnkgl3hOpkooqy2gMADg7RmCANq5bsOMXpAKApmIEBgDgNLid0jbY4veZAAMAcLjaxd8utjw+WoezZ2umxjdnheBa3EICADicu7u7fHx8dPLkSXl4eMjVlX9ft0Zms1lnz55Vbm6uAgICmrVqcS0CDADA4VxcXNS5c2elp6fr3//+t6PLgZ0FBAQoNDT0kj6DAAMAcAqenp7q3r07t5FaOQ8Pj0saealFgAEAOA1XV9cLlpYH6sJNRgAAYDgEGAAAYDgEGAAAYDgEGAAAYDgEGAAAYDgEGAAAYDgEGAAAYDgEGAAAYDgEGAAAYDgEGAAAYDgEGAAAYDgEGAAAYDgEGAAAYDgEGAAAYDgEGAAAYDgEGAAAYDgEGAAAYDgEGAAAYDgEGAAAYDgEGAAAYDgEGAAAYDgEGAAAYDgEGAAAYDhNDjB79uzRmDFjFBYWJhcXF23evNnqvNls1pw5c9S5c2eZTCZFR0fr2LFjVm3OnDmj2NhY+fn5KSAgQJMnT1ZRUZFVm++++0433HCDvL29FR4eriVLljS9dwAAoFVqcoApLi7WgAEDtHLlyjrPL1myRMuXL9eqVauUnJwsX19fxcTEqLS01NImNjZWhw4d0vbt2/XJJ59oz549mjp1quV8YWGhbr31Vl1++eVKTU3VX/7yF82bN09vvPFGM7oIAABaG/emvuG2227TbbfdVuc5s9msxMREzZo1S3feeack6Z133lFISIg2b96sCRMm6PDhw9q6dav279+vwYMHS5JWrFih22+/XUuXLlVYWJjWr1+v8vJyvf322/L09FTfvn2Vlpaml19+2SroAACAtsmmz8Ckp6crOztb0dHRlmP+/v4aOnSokpKSJElJSUkKCAiwhBdJio6Olqurq5KTky1tbrzxRnl6elraxMTE6MiRI8rLy6vz2mVlZSosLLR6AQCA1smmASY7O1uSFBISYnU8JCTEci47O1vBwcFW593d3RUYGGjVpq7POPca51u8eLH8/f0tr/Dw8EvvEAAAcEqtZhbSzJkzVVBQYHllZmY6uiQAAGAnNg0woaGhkqScnByr4zk5OZZzoaGhys3NtTpfWVmpM2fOWLWp6zPOvcb5vLy85OfnZ/UCAACtk00DTEREhEJDQ7Vjxw7LscLCQiUnJysqKkqSFBUVpfz8fKWmplra7Ny5U9XV1Ro6dKilzZ49e1RRUWFps337dvXs2VMdOnSwZckAAMCAmhxgioqKlJaWprS0NEk1D+6mpaUpIyNDLi4uSkhI0PPPP6+PP/5YBw8e1MSJExUWFqaxY8dKknr37q1Ro0ZpypQpSklJ0d69exUfH68JEyYoLCxMknTffffJ09NTkydP1qFDh7Rx40YtW7ZM06dPt1nHAQCAcTV5GvWBAwc0cuRIy9e1oWLSpElau3atZsyYoeLiYk2dOlX5+fm6/vrrtXXrVnl7e1ves379esXHx+vmm2+Wq6urxo8fr+XLl1vO+/v7a9u2bYqLi9OgQYPUsWNHzZkzhynUAABAUjMCzIgRI2Q2m+s97+LiogULFmjBggX1tgkMDNSGDRsavE7//v31xRdfNLU8AADQBrSaWUgAAKDtIMAAAADDIcAAAADDIcAAAADDIcAAAADDIcAAAADDIcAAAADDIcAAAADDIcAAAADDIcAAAADDIcAAAADDIcAAAADDIcAAAADDIcAAAADDIcAAAADDIcAAAADDIcAAAADDIcAAAADDIcAAAADDcXd0AQAu0amjDZ/3CZICwlumFgBoIQQYwKh8giQPH2nTlIbbefhIcSmEGACtCgEGMKqA8JpgcvZ0/W1OHa0JOGdPE2AAtCoEGMDIAsIJJgDaJB7iBQAAhkOAAQAAhkOAAQAAhkOAAQAAhkOAAQAAhkOAAQAAhkOAAQAAhkOAAQAAhkOAAQAAhkOAAQAAhkOAAQAAhkOAAQAAhkOAAQAAhkOAAQAAhkOAAQAAhkOAAQAAhkOAAQAAhkOAAQAAhkOAAQAAhkOAAQAAhkOAAQAAhkOAAQAAhkOAAQAAhmPzAFNVVaXZs2crIiJCJpNJV155pRYuXCiz2WxpYzabNWfOHHXu3Fkmk0nR0dE6duyY1eecOXNGsbGx8vPzU0BAgCZPnqyioiJblwsAAAzI5gHmxRdf1Ouvv65XX31Vhw8f1osvvqglS5ZoxYoVljZLlizR8uXLtWrVKiUnJ8vX11cxMTEqLS21tImNjdWhQ4e0fft2ffLJJ9qzZ4+mTp1q63IBAIABudv6A/ft26c777xTo0ePliRdccUVeu+995SSkiKpZvQlMTFRs2bN0p133ilJeueddxQSEqLNmzdrwoQJOnz4sLZu3ar9+/dr8ODBkqQVK1bo9ttv19KlSxUWFmbrsgEAgIHYfATm2muv1Y4dO3T06FFJ0rfffqsvv/xSt912myQpPT1d2dnZio6OtrzH399fQ4cOVVJSkiQpKSlJAQEBlvAiSdHR0XJ1dVVycrKtSwYAAAZj8xGY5557ToWFherVq5fc3NxUVVWlP//5z4qNjZUkZWdnS5JCQkKs3hcSEmI5l52dreDgYOtC3d0VGBhoaXO+srIylZWVWb4uLCy0WZ8AAIBzsfkIzAcffKD169drw4YN+vrrr7Vu3TotXbpU69ats/WlrCxevFj+/v6WV3h4uF2vBwAAHMfmAeaZZ57Rc889pwkTJqhfv3564IEH9OSTT2rx4sWSpNDQUElSTk6O1ftycnIs50JDQ5Wbm2t1vrKyUmfOnLG0Od/MmTNVUFBgeWVmZtq6awAAwEnYPMCcPXtWrq7WH+vm5qbq6mpJUkREhEJDQ7Vjxw7L+cLCQiUnJysqKkqSFBUVpfz8fKWmplra7Ny5U9XV1Ro6dGid1/Xy8pKfn5/VCwAAtE42fwZmzJgx+vOf/6yuXbuqb9+++uabb/Tyyy/r4YcfliS5uLgoISFBzz//vLp3766IiAjNnj1bYWFhGjt2rCSpd+/eGjVqlKZMmaJVq1apoqJC8fHxmjBhAjOQAACA7QPMihUrNHv2bP3+979Xbm6uwsLC9Oijj2rOnDmWNjNmzFBxcbGmTp2q/Px8XX/99dq6dau8vb0tbdavX6/4+HjdfPPNcnV11fjx47V8+XJblwsAAAzI5gGmffv2SkxMVGJiYr1tXFxctGDBAi1YsKDeNoGBgdqwYYOtywMAAK0AeyEBAADDIcAAAADDsfktJACNkJ8pnT1d//lTR1uuFgAwIAIM0NLyM6WVQ6SKsw238/CRfIJapiYAMBgCDNDSzp6uCS/j3pQ69qi/nU+QFMCK0gBQFwIM4Cgde0hhkY6uAgAMiYd4AQCA4RBgAACA4RBgAACA4RBgAACA4RBgAACA4RBgAACA4RBgAACA4bAODAB5FGWpr0u6vE/5Sy7t6m7EwnoAnAgBBmjjPIqy1P3Dm7TFq0T6qKGGPlJcCiEGgFMgwABtnFvpGblWlmha+e/1h3tGq1unOkZgTh2VNk2p2QaBAAPACRBgAEiSjpu7qLRjPynM39GlAMBF8RAvAAAwHAIMAAAwHAIMAAAwHAIMAAAwHAIMAAAwHAIMAAAwHAIMAAAwHAIMAAAwHAIMAAAwHFbiBdqCU0cvOOR9qkh9XdLllV/P5o0A4MQIMEBr5hNUswnjpikXnOomaYuXpM+laneT8krbt3h5ANBcBBigNQsIr9lB+uzpC04dP1mkae+nadmESFV5B+qXNekOKBAAmocAA7R2AeF17iBdai7QIXNBzQaOkiQCDADj4CFeAABgOAQYAABgOAQYAABgOAQYAABgOAQYAABgOMxCAtB4dSyIZ8UnqM4ZTwBgawQYABfXwIJ4Vjx8atadIcQAsDMCDICLa2BBPItTR2sCztnTBBgAdkeAAdA49SyIBwCOwEO8AADAcAgwAADAcAgwAADAcAgwAADAcAgwAADAcAgwAADAcJhGDdhafubF10sBAFwSAgxgS/mZ0sohUsXZhtt5+NSsbgsAaBa73ELKysrS/fffr6CgIJlMJvXr108HDhywnDebzZozZ446d+4sk8mk6OhoHTt2zOozzpw5o9jYWPn5+SkgIECTJ09WUVGRPcoFbOfs6ZrwMu5Naeru+l8stw8Al8TmIzB5eXm67rrrNHLkSP3jH/9Qp06ddOzYMXXo0MHSZsmSJVq+fLnWrVuniIgIzZ49WzExMfrhhx/k7e0tSYqNjdWJEye0fft2VVRU6KGHHtLUqVO1YcMGW5cM2F7HHlJYpKOrAIBWy+YB5sUXX1R4eLjWrFljORYREWH5tdlsVmJiombNmqU777xTkvTOO+8oJCREmzdv1oQJE3T48GFt3bpV+/fv1+DBgyVJK1as0O23366lS5cqLCzM1mUDAAADsfktpI8//liDBw/W7373OwUHB2vgwIF68803LefT09OVnZ2t6OhoyzF/f38NHTpUSUlJkqSkpCQFBARYwoskRUdHy9XVVcnJyXVet6ysTIWFhVYvAADQOtk8wPz00096/fXX1b17d/3zn//U448/rieeeELr1q2TJGVnZ0uSQkJCrN4XEhJiOZedna3g4GCr8+7u7goMDLS0Od/ixYvl7+9veYWH83wBAACtlc0DTHV1ta6++motWrRIAwcO1NSpUzVlyhStWrXK1peyMnPmTBUUFFhemZmZdr0eAABwHJsHmM6dO6tPnz5Wx3r37q2MjAxJUmhoqCQpJyfHqk1OTo7lXGhoqHJzc63OV1ZW6syZM5Y25/Py8pKfn5/VCwAAtE42DzDXXXedjhw5YnXs6NGjuvzyyyXVPNAbGhqqHTt2WM4XFhYqOTlZUVFRkqSoqCjl5+crNTXV0mbnzp2qrq7W0KFDbV0yAAAwGJvPQnryySd17bXXatGiRbr77ruVkpKiN954Q2+88YYkycXFRQkJCXr++efVvXt3yzTqsLAwjR07VlLNiM2oUaMst54qKioUHx+vCRMmMAMJAADYPsBcc801+uijjzRz5kwtWLBAERERSkxMVGxsrKXNjBkzVFxcrKlTpyo/P1/XX3+9tm7dalkDRpLWr1+v+Ph43XzzzXJ1ddX48eO1fPlyW5cLwAay8ktUcrJI3SQdP1kkk0+JugSYHF0WgFbMLlsJ3HHHHbrjjjvqPe/i4qIFCxZowYIF9bYJDAxk0TqghR3P/e9q1x18PRsVQrLySxT90m79pvK4tnhJ095P00/uRfrsqeGEGAB2w15IgMFl5Zcor7hcUuNDx/k6+HrK5OGmhI1plmMmD7dGhZC84nKVVFTp6Zie0m7p6Vt76qF/liuvuJwAA8BuCDCAgdWOfpRUVElqfOg4X5cAkz57arglCB3PLVLCxrQmhZDwQNM5/y1v0vUBoKkIMICB1Y5+JN4TKUlNDh3n6hJgYsQEgGEQYIBWoFtwO0eXAAAtyubrwAAAANgbAQYAABgOAQYAABgOz8AABnPutOlz120BgLaEAAMYyPnTpqWaqdMdfD0toQYA2gICDGAg506brp15VLt4HQEGQFtCgAEMqFtwO13Vxd/RZQCAw/AQLwAAMBwCDAAAMBwCDAAAMBwCDAAAMBwCDAAAMBwCDAAAMBwCDAAAMBwCDAAAMBwCDAAAMBwCDAAAMBwCDAAAMBwCDAAAMBw2cwRameO5RfWeq925GgCMjgADtBIdfD1l8nBTwsa0etuYPNz02VPDCTEADI8AA7QSXQJM+uyp4corLq/z/PHcIiVsTNP+9DPKC27X4EgNADg7AgzQinQJMNU7ulLXCI3Jw00dfD3r/bxzQw63nwA4EwIM0EbUNUJTXyipL+xw+wmAsyDAAG1IQyM057c7N+zU3n7KKy5XlwCTsvJLrM4BQEsjwACoU31hJyu/RNEv7VZJRZXlmMnDTX4mj5YsD0AbR4AB0CR5xeUqqahS4j2R6hbcTlLNLafgs0ccXBmAtoQAA6BZugW301Vd/P974KzjagHQ9rASLwAAMBxGYADYlFf+cfV1KdLJo546fqrmGRo/k4eC23nVNPAJkgLCHVghgNaAAAPANnyCJA8fhX8+TVu8JO2up52HjxSXQogBcEkIMABsIyC8JpicPa3cojIVllRIkjLPlGjptiNaNiFS3Vx+kTZNkc6eJsAAuCQEGAC2ExAuBYQrWFLw/x0qzSrQoX+Wq7RjP8mlnSOrA9CKEGAANBqL1gFwFgQYABd1/tYCF9tDCQDsjQAD4KLO31qAjR0BOBoBBkCjNHYfJQBoCSxkBwAADIcAAwAADIcAAwAADIcAAwAADIeHeIGmyM+sWUW2PqeOtlwtANCG2X0E5oUXXpCLi4sSEhIsx0pLSxUXF6egoCC1a9dO48ePV05OjtX7MjIyNHr0aPn4+Cg4OFjPPPOMKisr7V0uUL/8TGnlEOmN4fW/Nk2p2evHJ8jR1QJAq2bXEZj9+/frr3/9q/r37291/Mknn9SWLVv04Ycfyt/fX/Hx8Ro3bpz27t0rSaqqqtLo0aMVGhqqffv26cSJE5o4caI8PDy0aNEie5YM1O/saanirDTuTaljj/rbsdsyANid3QJMUVGRYmNj9eabb+r555+3HC8oKNDq1au1YcMG3XTTTZKkNWvWqHfv3vrqq680bNgwbdu2TT/88IM+++wzhYSEKDIyUgsXLtSzzz6refPmydOTFUDhQB17SGGRjq4CANo0u91CiouL0+jRoxUdHW11PDU1VRUVFVbHe/Xqpa5duyopKUmSlJSUpH79+ikkJMTSJiYmRoWFhTp06FCd1ysrK1NhYaHVCwAAtE52GYF5//339fXXX2v//v0XnMvOzpanp6cCAgKsjoeEhCg7O9vS5tzwUnu+9lxdFi9erPnz59ugegAA4OxsPgKTmZmpadOmaf369fL29rb1x9dr5syZKigosLwyMzNb7NoAAKBl2TzApKamKjc3V1dffbXc3d3l7u6u3bt3a/ny5XJ3d1dISIjKy8uVn59v9b6cnByFhoZKkkJDQy+YlVT7dW2b83l5ecnPz8/qBQAAWiebB5ibb75ZBw8eVFpamuU1ePBgxcbGWn7t4eGhHTt2WN5z5MgRZWRkKCoqSpIUFRWlgwcPKjc319Jm+/bt8vPzU58+fWxdMgAAMBibPwPTvn17XXXVVVbHfH19FRQUZDk+efJkTZ8+XYGBgfLz89Mf/vAHRUVFadiwYZKkW2+9VX369NEDDzygJUuWKDs7W7NmzVJcXJy8vLxsXTIAADAYh6zE+8orr8jV1VXjx49XWVmZYmJi9Nprr1nOu7m56ZNPPtHjjz+uqKgo+fr6atKkSVqwYIEjygUAAE6mRQLMrl27rL729vbWypUrtXLlynrfc/nll+vTTz+1c2UAAMCI2MwRAAAYDps5Ak4uK79EecXlkqTjuUUOrgYAnAMBBnBiWfklin5pt0oqqizHTB5u6uDLdhoA2jYCDODE8orLVVJRpcR7ItUtuJ0kqYOvp7oEmBxcGQA4FgEGMIBuwe10VRd/R5cBAE6Dh3gBAIDhEGAAAIDhEGAAAIDhEGAAAIDhEGAAAIDhEGAAAIDhEGAAAIDhEGAAAIDhEGAAAIDhsBIv4IRqN3Bk80YAqBsBBnAy52/gyOaNAHAhAgzgZM7fwLFVbt546mjD532CpIDwlqkFgCERYAAn1So3cPQJkjx8pE1TGm7n4SPFpRBiANSLAAOg5QSE1wSTs6frb3PqaE3AOXuaAAOgXgQYAC0rIJxgAuCSEWAAtIjaGVWt8pkeAC2OAAPArjr4esrk4aaEjWmSamZVffbUcEIMgEtCgAFq5Wde/NkMNFmXAJM+e2q4ZV2bhI1pyisuJ8AAuCQEGECqCS8rh0gVZxtu5+FTM5PGxmoXrpPUKhev6xJgIrAAsCkCDCDVjLxUnJXGvSl17FF/OzusT3L+wnUSi9cBwMUQYNA2NPb2UMceUlhki5RU6/yF6yQedAWAiyHAoPVz8O2hxmqVC9cBgJ0QYND6OfD2EADAPggwaDsccHsIAGAfro4uAAAAoKkIMAAAwHAIMAAAwHB4BgZwgNa+cB0A2BsBBsZnsC0AWLgOAC4dAQbGZpA1Xs7FwnUAcOkIMDA2A6/xwsJ1ANB8BBi0DqzxAgBtCrOQAACA4RBgAACA4RBgAACA4RBgAACA4RBgAACA4RBgAACA4RBgAACA4RBgAACA4RBgAACA4dg8wCxevFjXXHON2rdvr+DgYI0dO1ZHjhyxalNaWqq4uDgFBQWpXbt2Gj9+vHJycqzaZGRkaPTo0fLx8VFwcLCeeeYZVVZW2rpcAABgQDbfSmD37t2Ki4vTNddco8rKSv3xj3/Urbfeqh9++EG+vr6SpCeffFJbtmzRhx9+KH9/f8XHx2vcuHHau3evJKmqqkqjR49WaGio9u3bpxMnTmjixIny8PDQokWLbF0yAGd0sV3EnXB/KwAtx+YBZuvWrVZfr127VsHBwUpNTdWNN96ogoICrV69Whs2bNBNN90kSVqzZo169+6tr776SsOGDdO2bdv0ww8/6LPPPlNISIgiIyO1cOFCPfvss5o3b548PT1tXTYAZ+ETVLN7+KYpDbfz8JHiUggxQBtl980cCwoKJEmBgYGSpNTUVFVUVCg6OtrSplevXuratauSkpI0bNgwJSUlqV+/fgoJCbG0iYmJ0eOPP65Dhw5p4MCBF1ynrKxMZWVllq8LCwvt1SUA9hQQXhNMzp6uv82pozUB5+xpAgzQRtk1wFRXVyshIUHXXXedrrrqKklSdna2PD09FRAQYNU2JCRE2dnZljbnhpfa87Xn6rJ48WLNnz/fxj0A4BAB4QQTAA2y6yykuLg4ff/993r//ffteRlJ0syZM1VQUGB5ZWZm2v2aAADAMew2AhMfH69PPvlEe/bs0WWXXWY5HhoaqvLycuXn51uNwuTk5Cg0NNTSJiUlxerzamcp1bY5n5eXl7y8vGzcCwD2cDy3yPLrDr6e6hJgcmA1AIzI5iMwZrNZ8fHx+uijj7Rz505FRERYnR80aJA8PDy0Y8cOy7EjR44oIyNDUVFRkqSoqCgdPHhQubm5ljbbt2+Xn5+f+vTpY+uSgRaRlV+i77MKrH54tzUdfD1l8nBTwsY03bHiS92x4ktFv7RbWfklji4NgMHYfAQmLi5OGzZs0N///ne1b9/e8syKv7+/TCaT/P39NXnyZE2fPl2BgYHy8/PTH/7wB0VFRWnYsGGSpFtvvVV9+vTRAw88oCVLlig7O1uzZs1SXFwcoywwpKz8EkW/tFslFVWSJJOHmzr4tr3ZdF0CTPrsqeHKKy6XVDMSk7AxTXnF5YzCAGgSmweY119/XZI0YsQIq+Nr1qzRgw8+KEl65ZVX5OrqqvHjx6usrEwxMTF67bXXLG3d3Nz0ySef6PHHH1dUVJR8fX01adIkLViwwNblAi0ir7hcJRVVSrwnUt2C27Xp2yZdAkxttu8AbMfmAcZsNl+0jbe3t1auXKmVK1fW2+byyy/Xp59+asvSAIfrFtxOV3Xxd3QZAGB47IUEAAAMhwADAAAMx+4r8QKXJD/z4iuyAgDaHAIMnFd+prRyiFRxtuF2Hj41++c4maz8EqvZNgAA2yHAwHmdPV0TXsa9KXXsUX87J9yV+Pxp01LbnToNAPZAgIHz69hDCot0dBVNcv60aYkVZwHAlggwgB0xbRoA7INZSAAAwHAIMAAAwHAIMAAAwHB4BgZA63WxdYQkp5zFBuDiCDAAWqemrCMUl0KIAQyGAAM007kL1Z2PheucQGPWETp1VNo0RcpIanikhlEawOkQYIBmqGuhuvOxcJ2TaGgdIZ+gmhGYTVMa/gxGaQCnQ4ABmqB21OV4btEFC9Wdj4XrWkBDe2E1Zp+sgPCaYHKx/bY2TalpQ4ABnAYBBmik80ddTB5uuiYikJDiCE0ZObnYPlkB4Y0LJhcLRNxmAloUAQZopPO3B2CExYEaM3Ii2SZUcJsJcEoEGKCJ2B7ASTR25MQW1+E2E+B0CDAAcDEtFZYANBor8QIAAMMhwAAAAMPhFhJwjvMXp+NBXQBwTgQYOM7F9qlpzDoeNlTX4nQmDzetemCQgnw9WV0Xl469mQCbIcDAMZqyT83F1vGwkfOnSZ8uLtdj76Zq0tspljasrosGNRS6z56SNj5gm72ZCEIAAQYO0ph9aiSH/CV87jTpz54azi0lXFxT1oq5/2+ST8e6zzdmOjabVAKSCDBwtIb2qXECXQJMBBZcnK0X1rvYFgmN3aSSdWnQihFgAMAWbLFWTFNGcrpGEU7QphFgYB9O9oAuYAgtuUUCYHAEGNieEz6gCxgGq/4CjUKAQdM1ZnTFSR/QBQC0DgQYNE1TRle4Rw8AsBMCDJrGiac/AwDaDgIMmsfJpz83Re32Aay0CwDGQYBBm3b+9gGstItW5WKz/RgphYERYNCmnb99ACvtolVoynoy97xb/8rAtZ9FyIETIsAAst4+ADC8xqwnU7s30/8b3/BnEXLgpAgwsMYCdHCAc58/YhTMRhqznowtQw77LqGFEWDwXyxAhxbWwddTJg83JWxMsxwzebjps6eGE2Jagi1CTmP3XWIHbdgYAQb/1UamSNfOOpLEzCMH6xJgstrx+3hukRI2pimvuJwA4yxssTKwLXfQJgjh/xBgcKFWNEX6fOfPOpKYeeRo7PjdBjTmH0e1IzkZSfUHlNpbWrYIQjA8Akxb0Zh/tbTS51vOH3E5d9aRxDMXgE009PdH7bmG/nHUlJlT9/+t/oeKG3tLC4ZHgGkLGjt8K7W651vqG3G5JiKQ0ALYQlOCR0N/t9h6J27WwGn1CDDOrjEjJxfT2M0VJaf9n/rcURSp4VETRlyAFmTL4GGL521suQZOY6/nhH9ntgUEGGfWlJGTizHw5or1jaLUNVOFERfAAWwRPGzFlmvgNAbP2zgMAcZeWnrk5GIM/K+E81fLrWumyrn7GTHiArRxtpge3hg8b+NQBBh7YOSkWS52m6i+1XLr2s+IERcADbLlqBHP2ziEUweYlStX6i9/+Yuys7M1YMAArVixQkOGDHF0WRfX2PVUGqON/MGv79bPqgcGWYWaurCfUetTuz4Pv5dwak153obbTDbntAFm48aNmj59ulatWqWhQ4cqMTFRMTExOnLkiIKDgx1dXuO04vVUbKGhh21PF5frsXdTNentFEl1r9VS+0Ou9r/sZ2R856/My6q8cGqNed6G20x247QB5uWXX9aUKVP00EMPSZJWrVqlLVu26O2339Zzzz3n2OLYL6he598Gqk9tQGnoYdtzV2g991/i9S0/z2J0xnfuyrysygtDaOytqJb6udBGRu0lJw0w5eXlSk1N1cyZMy3HXF1dFR0draSkpDrfU1ZWprKyMsvXBQUFkqTCwkLbFpf/H+nNkVJlScPt3E1Spadk6+s30snCUp0sKrt4Qxs6c7ZCCe9/o9KK6ka19/Zw1WsTBirQx0OSFODjqfauFSosrJAktXeV2rd3+b/W1sc/mjJQ+Wf/G5TOfy+Mq/b3vejXalWXndV3P51Q0a91/3/UqZ2XOvl5t3CFQBNUekpV3tJ7j7TM9dxN0rg3WmY9r3YhUvsQm39s7c9ts9nccEOzE8rKyjJLMu/bt8/q+DPPPGMeMmRIne+ZO3euWRIvXrx48eLFqxW8MjMzG8wKTjkC0xwzZ87U9OnTLV9XV1frzJkzCgoKkouLSwPvbJ7CwkKFh4crMzNTfn5+Nv98Z0AfW4+20E/62Dq0hT5KbaOfze2j2WzWr7/+qrCwsAbbOWWA6dixo9zc3JSTk2N1PCcnR6GhoXW+x8vLS15eXlbHAgIC7FWihZ+fX6v9w1eLPrYebaGf9LF1aAt9lNpGP5vTR39//4u2cW1uQfbk6empQYMGaceOHZZj1dXV2rFjh6KiohxYGQAAcAZOOQIjSdOnT9ekSZM0ePBgDRkyRImJiSouLrbMSgIAAG2X0waYe+65RydPntScOXOUnZ2tyMhIbd26VSEhtn/iuTm8vLw0d+7cC25btSb0sfVoC/2kj61DW+ij1Db6ae8+upjNF5unBAAA4Fyc8hkYAACAhhBgAACA4RBgAACA4RBgAACA4RBgGrBy5UpdccUV8vb21tChQ5WSklJv2xEjRsjFxeWC1+jRo1uw4qZrSh8lKTExUT179pTJZFJ4eLiefPJJlZaWtlC1zdOUPlZUVGjBggW68sor5e3trQEDBmjr1q0tWG3T7dmzR2PGjFFYWJhcXFy0efPmi75n165duvrqq+Xl5aVu3bpp7dq1dq/zUjS1jydOnNB9992nHj16yNXVVQkJCS1S56Vqaj83bdqkW265RZ06dZKfn5+ioqL0z3/+s2WKbaam9vHLL7/Uddddp6CgIJlMJvXq1UuvvPJKyxTbTM35f7LW3r175e7ursjISLvVZytN7eeuXbvq/DmZnZ3drOsTYOqxceNGTZ8+XXPnztXXX3+tAQMGKCYmRrm5uXW237Rpk06cOGF5ff/993Jzc9Pvfve7Fq688Zraxw0bNui5557T3LlzdfjwYa1evVobN27UH//4xxauvPGa2sdZs2bpr3/9q1asWKEffvhBjz32mO666y598803LVx54xUXF2vAgAFauXJlo9qnp6dr9OjRGjlypNLS0pSQkKBHHnnEqX/wNbWPZWVl6tSpk2bNmqUBAwbYuTrbaWo/9+zZo1tuuUWffvqpUlNTNXLkSI0ZM6ZV/Xn19fVVfHy89uzZo8OHD2vWrFmaNWuW3njjDTtX2nxN7WOt/Px8TZw4UTfffLOdKrOt5vbzyJEjVj8vg4ODm1eAbbZfbH2GDBlijouLs3xdVVVlDgsLMy9evLhR73/llVfM7du3NxcVFdmrxEvW1D7GxcWZb7rpJqtj06dPN1933XV2rfNSNLWPnTt3Nr/66qtWx8aNG2eOjY21a522Isn80UcfNdhmxowZ5r59+1odu+eee8wxMTF2rMx2GtPHcw0fPtw8bdo0u9VjL03tZ60+ffqY58+fb/uC7KC5fbzrrrvM999/v+0LsoOm9PGee+4xz5o1yzx37lzzgAED7FqXrTWmn59//rlZkjkvL88m12QEpg7l5eVKTU1VdHS05Zirq6uio6OVlJTUqM9YvXq1JkyYIF9fX3uVeUma08drr71WqampllswP/30kz799FPdfvvtLVJzUzWnj2VlZfL29rY6ZjKZ9OWXX9q11paUlJRk9T2RpJiYmEb/2Ybzqq6u1q+//qrAwEBHl2I333zzjfbt26fhw4c7uhSbWrNmjX766SfNnTvX0aXYXWRkpDp37qxbbrlFe/fubfbnOO1KvI506tQpVVVVXbDqb0hIiP71r39d9P0pKSn6/vvvtXr1anuVeMma08f77rtPp06d0vXXXy+z2azKyko99thjTnsLqTl9jImJ0csvv6wbb7xRV155pXbs2KFNmzapqqqqJUpuEdnZ2XV+TwoLC1VSUiKTyeSgynCpli5dqqKiIt19992OLsXmLrvsMp08eVKVlZWaN2+eHnnkEUeXZDPHjh3Tc889py+++ELu7q33x3Lnzp21atUqDR48WGVlZXrrrbc0YsQIJScn6+qrr27y5zECYwerV69Wv379NGTIEEeXYlO7du3SokWL9Nprr+nrr7/Wpk2btGXLFi1cuNDRpdnMsmXL1L17d/Xq1Uuenp6Kj4/XQw89JFdX/leBc9uwYYPmz5+vDz74oPnPFDixL774QgcOHNCqVauUmJio9957z9El2URVVZXuu+8+zZ8/Xz169HB0OXbVs2dPPfrooxo0aJCuvfZavf3227r22mub/VB26416l6Bjx45yc3NTTk6O1fGcnByFhoY2+N7i4mK9//77WrBggT1LvGTN6ePs2bP1wAMPWP7l069fPxUXF2vq1Kn605/+5HQ/5JvTx06dOmnz5s0qLS3V6dOnFRYWpueee06/+c1vWqLkFhEaGlrn98TPz4/RF4N6//339cgjj+jDDz+84PZgaxERESGp5u+dnJwczZs3T/fee6+Dq7p0v/76qw4cOKBvvvlG8fHxkmpuBZrNZrm7u2vbtm266aabHFyl/QwZMqTZt+id6yeOk/D09NSgQYO0Y8cOy7Hq6mrt2LFDUVFRDb73ww8/VFlZme6//357l3lJmtPHs2fPXhBS3NzcJElmJ9xS61J+H729vdWlSxdVVlbqb3/7m+688057l9tioqKirL4nkrR9+/aLfk/gnN577z099NBDeu+995x+2QZbqa6uVllZmaPLsAk/Pz8dPHhQaWlpltdjjz2mnj17Ki0tTUOHDnV0iXaVlpamzp07N+u9jMDUY/r06Zo0aZIGDx6sIUOGKDExUcXFxXrooYckSRMnTlSXLl20ePFiq/etXr1aY8eOVVBQkCPKbpKm9nHMmDF6+eWXNXDgQA0dOlTHjx/X7NmzNWbMGEuQcTZN7WNycrKysrIUGRmprKwszZs3T9XV1ZoxY4Yju9GgoqIiHT9+3PJ1enq60tLSFBgYqK5du2rmzJnKysrSO++8I0l67LHH9Oqrr2rGjBl6+OGHtXPnTn3wwQfasmWLo7pwUU3to1TzF2Pte0+ePKm0tDR5enqqT58+LV1+ozW1nxs2bNCkSZO0bNkyDR061LKehslkkr+/v0P6cDFN7ePKlSvVtWtX9erVS1LN1PGlS5fqiSeecEj9jdGUPrq6uuqqq66yen9wcLC8vb0vOO5smvp7mZiYqIiICPXt21elpaV66623tHPnTm3btq15BdhkLlMrtWLFCnPXrl3Nnp6e5iFDhpi/+uory7nhw4ebJ02aZNX+X//6l1mSedu2bS1cafM1pY8VFRXmefPmma+88kqzt7e3OTw83Pz73//eZlPi7KUpfdy1a5e5d+/eZi8vL3NQUJD5gQceMGdlZTmg6sarnZp4/qu2X5MmTTIPHz78gvdERkaaPT09zb/5zW/Ma9asafG6m6I5fayr/eWXX97itTdFU/s5fPjwBts7o6b2cfny5ea+ffuafXx8zH5+fuaBAweaX3vtNXNVVZVjOtAIzfnzei6jTKNuaj9ffPFFy8+PwMBA84gRI8w7d+5s9vVdzGYnHPsHAABoAM/AAAAAwyHAAAAAwyHAAAAAwyHAAAAAwyHAAAAAwyHAAAAAwyHAAAAAwyHAAAAAwyHAAAAAwyHAAAAAwyHAAAAAwyHAAAAAw/n/dNgm1DFyNYsAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unpatched, patched use avgs are 1.00101 1.00075 and their SDs are 0.09408 0.03988\n",
      "And here is the pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 10084\n",
      "working on HD 300 out of 10084\n",
      "working on HD 600 out of 10084\n",
      "working on HD 900 out of 10084\n",
      "working on HD 1200 out of 10084\n",
      "working on HD 1500 out of 10084\n",
      "working on HD 1800 out of 10084\n",
      "working on HD 2100 out of 10084\n",
      "working on HD 2400 out of 10084\n",
      "working on HD 2700 out of 10084\n",
      "working on HD 3000 out of 10084\n",
      "working on HD 3300 out of 10084\n",
      "working on HD 3600 out of 10084\n",
      "working on HD 3900 out of 10084\n",
      "working on HD 4200 out of 10084\n",
      "working on HD 4500 out of 10084\n",
      "working on HD 4800 out of 10084\n",
      "working on HD 5100 out of 10084\n",
      "working on HD 5400 out of 10084\n",
      "working on HD 5700 out of 10084\n",
      "working on HD 6000 out of 10084\n",
      "working on HD 6300 out of 10084\n",
      "working on HD 6600 out of 10084\n",
      "working on HD 6900 out of 10084\n",
      "working on HD 7200 out of 10084\n",
      "working on HD 7500 out of 10084\n",
      "working on HD 7800 out of 10084\n",
      "working on HD 8100 out of 10084\n",
      "working on HD 8400 out of 10084\n",
      "working on HD 8700 out of 10084\n",
      "working on HD 9000 out of 10084\n",
      "working on HD 9300 out of 10084\n",
      "working on HD 9600 out of 10084\n",
      "working on HD 9900 out of 10084\n",
      "all done checking HD and complement contiguity for all 10084 HDs\n"
     ]
    }
   ],
   "source": [
    "patchedUse, unpUse = [0.]*nUnits, [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        patchedUse[u] += HDweight[t] * nDistricts\n",
    "    for u in unpatchedHDlist[t]:\n",
    "        unpUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(patchedUse,bins=50, label=\"patched\",histtype=\"step\")\n",
    "plt.hist(unpUse, bins=50, label=\"unpatched\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "patchedAvg, patchedSD = getWeightedAvgAndSD(patchedUse,unitPop)\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unpUse,unitPop)\n",
    "print(\"unpatched, patched use avgs are\",r5(unpatchedAvg), r5(patchedAvg),\"and their SDs are\",r5(unpatchedSD), r5(patchedSD) )\n",
    "print(\"And here is the pop distro\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP, ls=\"--\",color=\"orange\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%300 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs)  #these HDunitLists now appear to be sets\n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "ac9cd133-94f0-494b-ac74-0c584482d97e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets write these UNIT lists to a file\n"
     ]
    }
   ],
   "source": [
    "print(\"Lets write these UNIT lists to a file\")\n",
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"fullyPatched.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "id": "26b87c95-101f-4f8f-bb73-feb1827ac6b5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 if there were NO fragmented VTDs 0\n"
     ]
    }
   ],
   "source": [
    "noFrag = int(input(\"enter 1 if there were NO fragmented VTDs\"))\n",
    "if noFrag == 1:\n",
    "    nFragmentedVTDs,fragmentedVTDs = 0, list()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "ec102553-e4f3-4010-86bc-725a01b95788",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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oqCj87//+r+W5iRMnIigoCBs3boQQAjExMXjhhRfw5z//GQCg1+sRFRWFDRs2YPLkySgpKUF8fDwOHjyIgQMHAgCys7MxZswY/Pjjj4iJicGaNWuwcOFC6HQ6KJXXVszPmzcPW7duxcmTJ23qq8FggEajgV6vh1qtlnkaiIjIBpU1RgxYniOlLa6/8R22fn9LH8m57777kJubi9OnTwMAjh49iq+++gqjR48GAJSWlkKn0yEpKcnyGo1Gg8GDByMvLw8AkJeXh7CwMEvAAYCkpCT4+fkhPz/fUjNixAhLwAGA5ORknDp1CpcvX262b1evXoXBYLB6EBGRa/RbuktKwBkWF8qAQ82SPqY3b948GAwG9O7dG/7+/jCZTHjllVeQmpoKANDpdACAqKgoq9dFRUVZjul0OkRGRlp3NCAA4eHhVjVxcXE3tdF0rFOnTjf1LSMjA0uXLpXwKYmIyB6ypqdKlqUgSOkvpS3yPtJDzscff4xNmzZh8+bNuOuuu3DkyBHMnj0bMTExmDp1quy3a5P58+djzpw5ln8bDAZ069bNhT0iIvItxkYz7li0Q0pbHL1xPWOjGe/v/w45xRUABEbFa/HHoXFQBrjHHWqkh5wXX3wR8+bNw+TJkwEAffv2xQ8//ICMjAxMnToVWq0WAFBeXo7o6GjL68rLy9GvXz8AgFarRUVFhVW7jY2NqKystLxeq9WivLzcqqbp3001NwoMDERgYKD9H5KIiNps4afHsamgTEpbDDiul5FVjHf3llo9d+iHKmTsOIkZI+Iwf0y8i3r2C+lRq7a2Fn5+1s36+/vDbDYDAOLi4qDVapGbm2s5bjAYkJ+fj8TERABAYmIiqqqqUFhYaKnZvXs3zGYzBg8ebKnZu3cvGhoaLDU5OTm48847m52qIiIi17ltfqaUgLNyfDwDjhtoLuA0EQDe3VuKjKxi53aqGdJDzrhx4/DKK68gMzMT33//PT777DP87W9/w8MPPwwAUCgUmD17NpYvX47PP/8cx48fx2OPPYaYmBiMHz8eANCnTx+kpKRg+vTpKCgowP79+zFr1ixMnjwZMTExAIA//OEPUCqVmDZtGk6cOIGPPvoIb7zxhtV0FBERuV7svEyYJVzH++2KMZg8JO7WheRQxkZziwHneu/tK4Wx0eyEHrVM+nTVm2++iZdffhnPPPMMKioqEBMTg6eeegrp6emWmpdeeglXrlzBjBkzUFVVhWHDhiE7OxsqlcpSs2nTJsyaNQsPPvgg/Pz8MHHiRKxevdpyXKPRYNeuXUhLS8O9996LiIgIpKenW91Lh4iIXKfOaEKf9GwpbXH0xn38M+97m+rM4lrttOG3ObZDrZB+nxxPwvvkEBE5Rup7B7D/20t2txMEoIQBx62k/6sI/5f3g021jyX2wLL/TpDeB1u/v3lbSCIikkrW5eGHF41EeIjy1oXkVD3Cgx1S6wjucY0XERF5BZnbMzDguKcpibE21fkpbK91FIYcIiKym762QWrAIfelDPDDUyNuvQB8+nDX3y+H01VERGSXoRm5UnYPj1ABh5Yw4HiCpnvgNHeVlQJwm/vkcOExFx4TEbWbrNGbo+mjoAnuIKUtch5X3fHY1u9vhhyGHCKiduH0FLmKy3YhJyIi71ZZY2TAIY/ANTlERGSzfkt3oaqu4daFtzAsLhQbnxohoUdELWPIISIim8gavSlZloIgpb+Utohaw5BDREStMjaacceiHVLa4vQUORNDDhERtWjhp8el7B4OMOCQ8zHkEBFRs26bL2f38EmDovHqhAH2N0TURgw5RER0E1nrb04vH+3yu96S7+L/eUREZFFnNEm9PJwBh1yJIzlERAQAmLL+APadvWR3OyoAJ7n+htwAQw4REUkbvTm8aCR3Dye3wZBDROTjePdi8lacLCUi8lH62gYGHPJqHMkhIvJBQzNycV5fb3c7ESrg0BIGHHJPDDlERD5G1ujN0fRR0AR3kNIWkSMw5BAR+RBOT5Ev4ZocIiIfUFljZMAhn8ORHCIiL9d/2S5crm2wu52hsSHY9PT9EnpE3sJkFigorURFdT0iQ1UYFBcOfz+Fq7tlwZBDROTFZI3elCxLQZDSX0pb5B2yiy5i6bZiXLxuAXu0RoXF4+KRkhDtwp79gtNVREReyGQWUqenGHDoetlFFzFz42GrgAMAOn09Zm48jOyiiy7qmTWGHCIiL/Nhfhl6LsiS0hbX39CNTGaBpduK0dwG9eI/j6XbimGSsYW9nThdRUTkRXotyEKjhC+XSYOi8eqEARJ6RN6moLTyphGcG13U16OgtBKJPTs7qVfNY8ghIvISsqanTi8fzd3DqUU6g203kbS1zpH4fzERkYerM5qkrr9hwKHWVNZclVrnSBzJISLyYFPWH8C+s5fsbkcF4CTX35ANwjvatsu8rXWOxJBDROShZI3eHF40EuEhrv9CIs+g1QRJrXMkjkkSEXkgmdNTDDjUFoPiwhGtUbVaE625dmNAV2PIISLyIDX1jdyegVzK30+BxePi0dJ9jRUAFo+Ld4s7HzPkEBF5iJTX9yBhyU6724lQMeCQfVISorHm0QE3jehEa1RY8+gAt7njMdfkEBF5AFmjN0fTR0ET3EFKW+TbUhKiMTJey72riIio/Tg9Re7K30/h8hv+tYbTVUREbqqyxsiAQ2QHjuQQEbmh/st24XJtg93tDI0Nwaan75fQIyLPw5BDRORmZI3elCxL4e7h5NMYcoiI3ITJLLh7OJFEXJNDROQGPswvY8AhkowjOURELtZrQRYazcLudiYNisarEwZI6BGRd2DIISJyIVnrb04vH83dw4luwJBDROQCdUYT+qRnS2mL01PkKsZGM/6Z9z1+qKxFj/BgTEmMdauwzZBDRORkU9YfwL6zl+xuRwGglAGHXCQjqxjv7SvF9TOtr2SVYPrwOMwfE++6jl2HIYeIyIlkTU8dXJCELupAKW0RtVVGVjHe3Vt60/NmAcvz7hB03GdMiYjIy8m8ezEDDrmKsdGM9/bdHHCu996+UhgbzU7qUcsYcoiIHKymvpHbM5DX+Gfe97jVxYBmca3O1ThdRUTkQCmv78HJ8hq724lQAYeWMOCQ631/qVZqnSMx5BAROYis0Zuj6aOgCe4gpS0i+9l6Tyf77/1kL05XERE5gMzpKQYccif9uoZJrXMkhhwiIokqa4xcf0NeLaZTsNQ6R+J0FRGRJP2X7cLl2ga72+kVHoB/v5QsoUdE8g2KC0dYcAdUtfL/eqfgDhgUF+7EXjWPIYeISAJZozdFS5IRouKvZvJsrl+Ncw2nq4iI7GAyC6nTUww45O4KSitbHcUBgKraBhSUVjqpRy1zSMg5f/48Hn30UXTu3BlBQUHo27cvDh06ZDkuhEB6ejqio6MRFBSEpKQknDlzxqqNyspKpKamQq1WIywsDNOmTUNNjfVlmMeOHcPw4cOhUqnQrVs3rFq1yhEfh4ioWR8VnEPPBVlS2uL6G/IUFdX1UuscSXrIuXz5MoYOHYoOHTpgx44dKC4uxl//+ld06tTJUrNq1SqsXr0aa9euRX5+Pjp27Ijk5GTU1/9yQlJTU3HixAnk5ORg+/bt2Lt3L2bMmGE5bjAYMGrUKPTo0QOFhYV47bXXsGTJEqxbt072RyIiuskdi3Zg7qfH7G5n0qBoBhzyKJGhKql1jqQQQkidOps3bx7279+Pffv2NXtcCIGYmBi88MIL+POf/wwA0Ov1iIqKwoYNGzB58mSUlJQgPj4eBw8exMCBAwEA2dnZGDNmDH788UfExMRgzZo1WLhwIXQ6HZRKpeW9t27dipMnT9rUV4PBAI1GA71eD7VaLeHTE5EvkDU9dXr5aLfasZnIFsZGM3q/vKPVux77KYCTf3Hc/9+2fn9Lf/fPP/8cAwcOxO9+9ztERkaif//+eO+99yzHS0tLodPpkJSUZHlOo9Fg8ODByMvLAwDk5eUhLCzMEnAAICkpCX5+fsjPz7fUjBgxwhJwACA5ORmnTp3C5cuXZX8sIiLUGU1S198w4JAnKvzhsk3bOhT+4PrvYuk/Yd999x3WrFmD22+/HTt37sTMmTPx7LPP4oMPPgAA6HQ6AEBUVJTV66KioizHdDodIiMjrY4HBAQgPDzcqqa5Nq5/jxtdvXoVBoPB6kFEZIsp6w+gT3q23e0owPU35Nk8aU2O9GX8ZrMZAwcOxIoVKwAA/fv3R1FREdauXYupU6fKfrs2ycjIwNKlS13aByLyPLJGbw4uSOLu4eTxPGlNjvSRnOjoaMTHx1s916dPH5SVlQEAtFotAKC8vNyqpry83HJMq9WioqLC6nhjYyMqKyutappr4/r3uNH8+fOh1+stj3PnzrXnIxKRD5E5PcWAQ95gUFw4ojUqKFo4rgAQrVG5xc0ApYecoUOH4tSpU1bPnT59Gj169AAAxMXFQavVIjc313LcYDAgPz8fiYmJAIDExERUVVWhsLDQUrN7926YzWYMHjzYUrN37140NPxyrX5OTg7uvPNOqyu5rhcYGAi1Wm31ICJqTk19I7dnIGqGv58Ci8fFt3jDPwFg8bh4+Pu1FIOcR3rIef7553HgwAGsWLECZ8+exebNm7Fu3TqkpaUBABQKBWbPno3ly5fj888/x/Hjx/HYY48hJiYG48ePB3Bt5CclJQXTp09HQUEB9u/fj1mzZmHy5MmIiYkBAPzhD3+AUqnEtGnTcOLECXz00Ud44403MGfOHNkfiYh8TMrre5CwZKfd7XQOZMAhciXpl5ADwPbt2zF//nycOXMGcXFxmDNnDqZPn245LoTA4sWLsW7dOlRVVWHYsGF45513cMcdd1hqKisrMWvWLGzbtg1+fn6YOHEiVq9ejZCQEEvNsWPHkJaWhoMHDyIiIgJ/+tOfMHfuXJv7yUvIiehGskZvjqaP4u7h5JVMZoFhr+7GRX3zC4sVALQaFb6a+/8cNppj6/e3Q0KOp2DIIaLrcXqK6Nbyvr2ER947cMu6D6cPQWLPzg7pg8vuk0NE5Gkqa4wMOEQ28ulLyImIPEn/Zbtw+RabDdqiV3gA/v1SsoQeEbk3T7qEnCGHiHyWrNGboiXJ3D2cfEbTJeQ6fX2zV1g1rcnxykvIiYjcnbHRLHV6igGHfEnTJeQAbrpXTtO/vfYSciIid7bw0+O4Y9EOKW1x/Q35qpSEaKx5dAC0GuspKa1GhTWPDkBKQrSLemaNf34Qkc+4bX7mLTcWtMWkQdF4dcIA+xsi8mApCdEYGa9FQWklKqrrERl6bYrKHUZwmjDkEJFPkDU9dXr5aO4eTvQf/n4Kh10mLgN/UonIq9UZTVLX3zDgEHkOjuQQkddKfe8A9n97SUpbXH9D5HkYcojIK8kavVn18F34/eBYKW0RkXMx5BCR15EVcL5dMcatFlESUdtwcpmIvIa+tkHq+hsGHCLPxpEcIvIKQzNycb6FXZHb4rYwP+yeN1pCj4jI1RhyiMjjcXsGImoOf5qJyKNx93AiagnX5BCRR/rJcJUBh4haxZEcIvI48enZqDWa7G5nWFwoNj41QkKPiMgdMeQQkUeRNXpTsiwFQUp/KW0RkXtiyCEij2BsNHP3cCJqE4YcInJ7Cz89jk0FZVLaYsAh8h0MOUTk1m6bnwmzsL+dlePjMXlInP0NEZHHYMghIrfF7RmIyB68hJyI3E6d0cTtGYjIbhzJISK3kvreAez/9pLd7QQBKOH6GyKfxpBDRG5D1ujN4UUjER6ilNIWEXkuhhwicgu8ezGRZzl1oRrJq/da/q0AkDlrOOK7ql3XqRsw5BCRS+lrG3DPsl1S2mLAIXKO5v4oEQDGvLUPgPv8LHLhMRG5zNCMXCkBJ0LlPr9UibydLaOuskZm7cWRHCJyCVm/BI+mj4ImuIOUtoiodacuVNtcW/yjweVTVxzJISKnk7n+hgGHyHlGv7n31kX/8dB/pq5ciSGHiJymssbIBcZEHqwtdx83O64bNuN0FRE5Rb+lu1BV12B3O8PiQrHxqRESekREjuQOoygMOUTkcLJGb0qWpSBI6S+lLSJqu0AAV22s3T5ruCO7YhN3CFpE5KWMjWap01MMOESutWfegzbXunrRMcCRHCJykIWfHsemgjIpbXH9DZF7eP/r72yqc5efWYYcIpLutvmZbVqg2JKV4+MxeUic/Q0Rkd2MjWa8u7f0lnV+imu1ygDXTxa5vgdE5FVi58kJON+uGMOAQ+RG3so9Y1OdWQD/zPvesZ2xEUMOEUlRZzRJXX/j76eQ0hYRybFm71mba3+orHVgT2zH6SoistuU9Qew7+wlu9tRATjpJnP5RGSt0WR7bY/wYMd1pA0YcojILrJGbw4vGonwEKWUtohIPj8AtuacKYmxDuyJ7ThdRUTtJnN6igGHyL31+1VHm+qiQgLcYtExwJBDRO2gr23g9gxEPqaT2raQ07dbuIN7YjtOVxFRmwzNyMV5fb3d7USogENLGHCIPMVtXToCJTbWuQmGHCKymazRm6Ppo7h7OJGHUfrbNvlja50zuE9PiMityZyeYsAh8jyJt0VIrXMGhhwialVljZHrb4gIQ3p2RvAt9o/rqPTHkJ6dndSjW+N0FRG1qN/SXaiqa7C7nWFxodj41AgJPSIiV1IG+KHW2PKF5B3c5KqqJgw5RNQsWaM3JctSuHs4kRcoKK1EVW3rf/RU1TagoLQSiW4ymsOQQ0RWTGaBnguypLTF6Ski71FRbdtVlbbWOYN7jSsRkUt9mF/GgENEzYoMVUmtcwaO5BARAKDXgiw0Stg+fNKgaLw6YYCEHhGROxkUF45ojQo6fT2a+02hAKDVqDAozn1uBsiRHCJC7LxMKQHn9PLRDDhEXsrfT4HF4+IBXAs012v69+Jx8fD3u/Go6zDkEPmwOqNJ6uXh7rJfDRE5RkpCNNY8OgBajfWUlFajwppHByAlIdpFPWsep6uIfNSU9Qew7+wlu9tRATjJ9TdEPiMlIRoj47UoKK1ERXU9IkOvTVG50whOE4YcIh8ka/Tm8KKR3D2cyAf5+ync5jLx1jDkEPkY3r2YiHyFwyfQV65cCYVCgdmzZ1ueq6+vR1paGjp37oyQkBBMnDgR5eXlVq8rKyvD2LFjERwcjMjISLz44otobGy0qvnyyy8xYMAABAYGolevXtiwYYOjPw6Rx9LXNjDgEJFPcWjIOXjwIN59913cfffdVs8///zz2LZtGz755BPs2bMHFy5cwIQJEyzHTSYTxo4dC6PRiK+//hoffPABNmzYgPT0dEtNaWkpxo4diwceeABHjhzB7Nmz8eSTT2Lnzp2O/EhEHmloRi7uWbbL7nYiVAw4ROQ5FEII+68bbUZNTQ0GDBiAd955B8uXL0e/fv3w97//HXq9Hl26dMHmzZvx29/+FgBw8uRJ9OnTB3l5eRgyZAh27NiBhx56CBcuXEBUVBQAYO3atZg7dy5++uknKJVKzJ07F5mZmSgqKrK85+TJk1FVVYXs7Gyb+mgwGKDRaKDX66FWq+WfBCI3IGv05mj6KO4eTkRuwdbvb4eN5KSlpWHs2LFISkqyer6wsBANDQ1Wz/fu3Rvdu3dHXl4eACAvLw99+/a1BBwASE5OhsFgwIkTJyw1N7adnJxsaaM5V69ehcFgsHoQeTOZ01MMOETkaRyy8HjLli04fPgwDh48eNMxnU4HpVKJsLAwq+ejoqKg0+ksNdcHnKbjTcdaqzEYDKirq0NQUNBN752RkYGlS5e2+3MReYrKGiMGLM+R0hanp4jIU0kfyTl37hyee+45bNq0CSqV++xfAQDz58+HXq+3PM6dO+fqLhFJ13/ZLikBZ2hsCAMOEXk06SM5hYWFqKiowIABv9za3WQyYe/evXjrrbewc+dOGI1GVFVVWY3mlJeXQ6vVAgC0Wi0KCgqs2m26+ur6mhuvyCovL4darW52FAcAAgMDERgYaPdnJHJXsqanSpalIEjpL6UtIiJXkT6S8+CDD+L48eM4cuSI5TFw4ECkpqZa/rtDhw7Izc21vObUqVMoKytDYmIiACAxMRHHjx9HRUWFpSYnJwdqtRrx8fGWmuvbaKppaoPIl5jMQur6GwYcIvIG0kdyQkNDkZCQYPVcx44d0blzZ8vz06ZNw5w5cxAeHg61Wo0//elPSExMxJAhQwAAo0aNQnx8PKZMmYJVq1ZBp9Nh0aJFSEtLs4zEPP3003jrrbfw0ksv4YknnsDu3bvx8ccfIzNTzi96Ik/xYX4Z5n92XEpbnJ4iIluYzILbOrTk9ddfh5+fHyZOnIirV68iOTkZ77zzjuW4v78/tm/fjpkzZyIxMREdO3bE1KlTsWzZMktNXFwcMjMz8fzzz+ONN95A165dsX79eiQnJ7viIxG5RK8FWVJ2D580KJq7hxORTbKLLmLptmJc1NdbnovWqLB4XLzbbdDpsPvkeALeJ4c8mazpqdPLR3P3cCKySXbRRczceBg3BoemMRxn7UTu8vvkEJFj1BlNUtffMOAQkS1MZoGl24pvCjgALM8t3VYMk4TRZVm4QSeRB5my/gD2nb1kdzsKAKVcf0NEbVBQWmk1RXUjAeCivh4FpZVus0M5Qw6Rh5A1enNwQRK6qHkrBSJqm4rqlgNOe+qcgSGHyANw93AicrUXPj5iU11kqPvcCJiT8URurKa+kQGHiFwudl4mGs23rvNTAIPiwh3fIRtxJIfITaW8vgcny2vsbidCBRxawoBDRO3Tlj+0zALQ1zYgPETpwB7ZjiGHyA3JGr05mj6Ku4cTUbu153fR5HVfY9ec/5LfmXZgyCFyM5yeIiJ3cFbXvpHkimqj5J60H9fkELmJyhojAw4RuY3Rq/e063WRoe4xVQVwJIfILfRftguXaxvsbmdobAg2PX2/hB4Rka9rsGGhcXO2zLhPbkfswJBD5GKyRm9KlqVw93AicqkuIUq3WXQMMOQQuYzJLNBzQZaUtjg9RUQyteePry4hShxcNNIBvWk/hhwiF/io4BzmfnpMSlsMOEQkU68FbQ84hxeNdKsRnCYMOUROdseiHTDacletW5g0KBqvThggoUdERNeU/Vxr003/rqcA3DLgAAw5RE4la/3N6eWjuXs4EUmX8kbbr6iK7Oi+awH5W5LICeqMJqmXhzPgEJEj1Lbjkqrtzz3ggJ7IwZEcIgebsv4A9p29ZHc7CgClXH9DRG6mizrQ1V1oEUMOkQPJGr05uCDJrX+REJF36BOhRMnPtt+x+As32b6hJRzzJnIQmdNTDDhE5AzvPznc5lo/BRAX2dGBvbEfQw6RZDX1jdyegYg80ltfnLG59rsM9//9xOkqIolSXt+Dk+Xt29TuehEq4NAS9/8FQkTeZWN+mU11CTFqB/dEDoYcIklkjd4cTR8FTXAHKW0REdnqfGWdzbU19fbvtecMDDlEEnB6iog8XXIb7pFjbGx0YE/k4ZocIjtU1hgZcIjIK9RcNdlcq+zgGWMkntFLIjfUf9kuXK61f8i2V3gA/v1SsoQeERG1z7o9J9tUn9izs4N6IhdDDlE7yBq9KVqSjBAVfwyJyHVMZoEVO75t02vSH0pwUG/k4m9XojYwmQV6LsiS0hanp4jIHeQWl7epPjgACFK6735V1+OaHCIbfVRwjgGHiLxO+udFbap/+N5uDuqJfBzJIbLBHYt2wNjY9o3rbjRpUDRenTBAQo+IiOSobuPl4IvG3uWgnsjHkEN0C7LW35xePpq7hxOR21EF+OGK0bY/4ob3ivCYqSqA01VELaozmqReHs6AQ0Tu6LbOQTbX/vPJwQ7siXwcySFqxpT1B7Dv7CUpbXH9DRG5s0Pnqm2qUzi4H47AkEN0A1mjN6sevgu/HxwrpS0iIkcRkuvcCUMO0XVkBZxvV4yBv58n/t1DRL4mQAE02pBgAjzwVxoXCRABqKlvlLr+hgGHiDxF9nP3S61zJxzJIZ+X8voenCyvsbudzoFA4VKuvyEiz9JLGwIFWp+OUvynztMw5JBPkzV6czR9FDTBHaS0RUTkbKUrxyJuXmazQUfxn+OeiCGHfBZ3Dyci+kXpyrE4q6vB6NV70GAGOvgBO5693yNHcJow5JDPqawxYsDyHCltMeAQkTfppQ3BmRXe83uNIYd8Sv9lu3C5tm23MG9Or/AA/PulZAk9IiIiR2HIIZ8ha3qqaEkyQlT80SEicnf8TU1ez2QW3D2ciMgH8T455NU+KjjHgENE5KM4kkNe645FO2BstG1n3db87tdavDbxXgk9IiIiZ2LIIa8ka/3N6eWjuXs4EfkMk1mgoLQSFdX1iAxVYVBcuEffwZ0hh7yKsdGMOxbtkNIWp6eIyJdkF13E0m3FuKivtzwXrVFh8bh4pCREu7Bn7cc/UclrLPj0GAMOEVE7ZBddxMyNh60CDgDo9PWYufEwsosuuqhn9uFIDnmFlm5H3larHr4Lvx8cK6ElIiLPYDILLN1W3OzvUIFr2zos3VaMkfFaj5u6Ysghjydr/c23K8Z43A8wEZG9CkorbxrBuZ4AcFFfj4LSSiT27Oy8jknA6SryWPraBqn7TzHgEJEvqqhuOeC0p86dcCSHPNLQjFycb+UvD1t1DgQKl3L9DRH5rshQldQ6d8KQQx5H1ujN0fRR0AR3kNIWEZGnGhQXjmiNCjp9fbPrchQAtJprl5N7Gk5XkUeROT3FgENEBPj7KbB4XDyAa4Hmek3/Xjwu3iOn9BlyyCNU1hilBhwiIvpFSkI01jw6AFqN9ZSUVqPCmkcHeOx9cjhdRW6v39JdqKprsLudXuEB+PdLyRJ6RETkfVISojEyXss7HhM5i6zRm6IlyQhR8X93IqLW+PspPO4y8dZIn67KyMjAr3/9a4SGhiIyMhLjx4/HqVOnrGrq6+uRlpaGzp07IyQkBBMnTkR5eblVTVlZGcaOHYvg4GBERkbixRdfRGNjo1XNl19+iQEDBiAwMBC9evXChg0bZH8cchFjo1nq9BQDDhGR75Eecvbs2YO0tDQcOHAAOTk5aGhowKhRo3DlyhVLzfPPP49t27bhk08+wZ49e3DhwgVMmDDBctxkMmHs2LEwGo34+uuv8cEHH2DDhg1IT0+31JSWlmLs2LF44IEHcOTIEcyePRtPPvkkdu7cKfsjkZMt/PQ4t2cgIiK7KYQQMu6G36KffvoJkZGR2LNnD0aMGAG9Xo8uXbpg8+bN+O1vfwsAOHnyJPr06YO8vDwMGTIEO3bswEMPPYQLFy4gKioKALB27VrMnTsXP/30E5RKJebOnYvMzEwUFRVZ3mvy5MmoqqpCdna2TX0zGAzQaDTQ6/VQq9XyPzy12W3zM2GW8H/kyvHxmDwkzv6GiIjI7dj6/e3wq6v0ej0AIDz82vX1hYWFaGhoQFJSkqWmd+/e6N69O/Ly8gAAeXl56Nu3ryXgAEBycjIMBgNOnDhhqbm+jaaapjaac/XqVRgMBqsHuY/YeXICzrcrxjDgEBGRY0OO2WzG7NmzMXToUCQkJAAAdDodlEolwsLCrGqjoqKg0+ksNdcHnKbjTcdaqzEYDKirq2u2PxkZGdBoNJZHt27d7P6MZL86o4nbMxARkXQODTlpaWkoKirCli1bHPk2Nps/fz70er3lce7cOVd3yeelvncAfdJtm15sTRC4/oaIiKw57JKTWbNmYfv27di7dy+6du1qeV6r1cJoNKKqqspqNKe8vBxardZSU1BQYNVe09VX19fceEVWeXk51Go1goKCmu1TYGAgAgMD7f5sJIes0ZvDi0YiPEQppS0iIvIe0kdyhBCYNWsWPvvsM+zevRtxcdZrI+6991506NABubm5ludOnTqFsrIyJCYmAgASExNx/PhxVFRUWGpycnKgVqsRHx9vqbm+jaaapjbIvcmcnmLAISKi5ki/uuqZZ57B5s2b8a9//Qt33nmn5XmNRmMZYZk5cyaysrKwYcMGqNVq/OlPfwIAfP311wCuXULer18/xMTEYNWqVdDpdJgyZQqefPJJrFixAsC1S8gTEhKQlpaGJ554Art378azzz6LzMxMJCfbdldbXl3lfPraBtyzbJeUtjg9RUTkm2z9/pYechSK5hd9vv/++/jjH/8I4NrNAF944QV8+OGHuHr1KpKTk/HOO+9YpqIA4IcffsDMmTPx5ZdfomPHjpg6dSpWrlyJgIBfZti+/PJLPP/88yguLkbXrl3x8ssvW97DFgw5zjU0Ixfn9fV2txOhAg4tYcAhIvJVLgs5noQhx3lkTU8dTR/F3cOJiHycrd/fvNc9ORx3DyciIldw+M0AyXdV1hgZcIiIyGU4kkMO0W/pLlTVNdjdzrC4UGx8aoSEHhERka9hyCHpZI3elCxLQZDSX0pbRETkexhySBpjo5m7hxMReTCTWaCgtBIV1fWIDFVhUFy4R2+Vw5BDUiz89Dg2FZRJaYsBh4jI+bKOXcSifxWh8orR8ly0RoXF4+KRkhDtwp61Hxcek91um58pJeBMGhTNgENE5AIZWcV4ZvNhq4ADABf19Zi58TCyiy66qGf24UgO2UXW+pvTy0dDGcDMTUTkbFnHLuDdvaUtHhcAlm4rxsh4rcdNXfFbhdqlzmiSenk4Aw4RkfOZzAJ/2vLNLesu6utRUFrphB7JxZEcarMp6w9g39lLdrejAnCS01NERC6z59RPMJltq62otn9bHmdjyKE2kTV6c3jRSO4eTkTkYhk7SmyujQxVObAnjsGQQzbj3YuJiLzLmYoam2sHxYU7sCeOwYUQdEv62gYGHCIiH+dpi44BjuTQLQzNyMV5vf3zsBEq4NASBhwiIndhMgtXd8HhGHKoRbJGb46mj4ImuIOUtoiISI71u7+1udbzxnCuYcihZnF6iojIu2X8+5TNtf26qh3YE8fhmhyyUlljZMAhIiIrG54Y4uoutAtHcsii/7JduFzbYHc7Q2NDsOnp+yX0iIiI3IGnLjlgyCEA8qanSpalIEjpL6UtIiJyjLM62y8d/79Hf+3AnjgWQ46PM5kFei7IktIWp6eIiDzD6NV7bK4dkRDpwJ44Ftfk+LAP88sYcIiIfFCDjVs5eDqO5PioXguy0CjhHgmTBkXj1QkDJPSIiIicoaa+0dVdcBqGHB8ka/3N6eWjuXs4EZGHSViy09VdcBp+Q/mQOqNJ6uXhDDhERJ7lvhVtCziefhkJR3J8xJT1B7Dv7CW721EBOMn1N0REHkdf24ALhrZNVSXEhDioN87BkOMDZI3eHF40EuEhSiltERGRcz2xoaDNr/m/J+9zQE+chyHHy/HuxUREBADnq+ra/BpPvQlgEy6q8FI19Y0MOEREZBHg17ZtNnc+O8JBPXEehhwvlPL6Himr5yNUDDhERN5iSK/wNtXfGRPqoJ44D6ervIys0Zuj6aM8fpiSiIh+0SdKA+CCTbXe8gcuR3K8iMzpKQYcIiLvMiUxFrbMWJ1ePtrxnXEShhwvUFlj5PobIiJqlTLAD9OHx7Va89SIOK+6Bxqnqzxc/2W7cLm2we52hsaGYNPT90voERERuav5Y+IBAO/tK8X1O/v4KYDpw+Msx72FQghh/wZGHspgMECj0UCv10OtVru6O20ma/SmZFkKgpSefl9LIiKylbHRjH/mfY8fKmvRIzwYUxJjPWoEx9bvb47keCCTWXD3cCIiajd/PwXiYzSICA1EZKgK/m28vNxTMOR4mA/zyzD/s+NS2mLAISLyPdlFF7F0WzEu6ustz0VrVFg8Lh4pCdEu7Jl8DDkepNeCLDSa7Z9dnDQoGq9OGCChR0RE5Emyiy5i5sbDuPGbRKevx8yNh7Hm0QFeFXQYcjyErPU3p5eP9qh5VyIiksNkFli6rfimgAMAAoACwNJtxRgZr/Wa6St+27m5OqNJ6uXhDDhERL6poLTSaorqRgLARX09CkorndcpB+NIjhubsv4A9p29ZHc7CgClXH9DROTT1u/71qa6iuqWg5CnYchxU7JGbw4uSEIXdaCUtoiIyDMZG83IPfmTTbWGK40O7o3zcO7CDcmcnmLAISKif+Z9b3Pty9uKHNcRJ2PIcSM19Y3cnoGIiKT7obLW1V1wCU5XuYmU1/fgZHmN3e1EqIBDSxhwiIjoFz3Cg13dBZdgyHEDskZvjqaP4u7hRER0kymJsfhLZolNtVufHurg3jgPp6tcTOb0FAMOERE1Rxngh6dGtL4DeZN+sWGO7YwTMeS4SGWNketviIjIaeaPib9l0PG27xPuQu6CXcj7L9uFy7UNdrczNDYEm56+X0KPiIjIVxgbzfjLjiP45/6Llue2Pj3Uo0ZwbP3+ZshxcsiRNXpTsiwFQUp/KW0RERF5Elu/v7nw2ElMZoGeC7KktOVtw4lERESOwJDjBB8VnMPcT49JaYsBh4iI7FH2cy1S3tiDugYzgjr4Ifu5+9E9wjsvMWfIcbA7Fu2AsdFsdzuTBkXj1QkDJPSIiIh8Va8Fmbj+K6m2wYwR//MFAvyAsyu8749ohhwHkrX+5vTy0dw9nIiI7HJjwLleo/nacW8LOvzmdIA6o0nq5eEMOEREZI+yn2tbDDhNGs3X6rwJvz0lm7L+APqkZ9vdjgJcf0NERHKkvLFHap2n8PiQ8/bbbyM2NhYqlQqDBw9GQUGBy/oSNy8T+85esrudgwuSUMqAQ0REktQ12LY21NY6T+HRIeejjz7CnDlzsHjxYhw+fBj33HMPkpOTUVFR4fS+9JyXCRk3HPp+5Vh0UQdKaImIiOiaoA62fd3bWucpPPrT/O1vf8P06dPx+OOPIz4+HmvXrkVwcDD+8Y9/OLUf5yvrYJLQDqeniIjIEcIDbfsz3NY6T+GxIcdoNKKwsBBJSUmW5/z8/JCUlIS8vLxmX3P16lUYDAarhwyjV9s3hxmhYsAhIiLHqTHZdjG1rXWewmNDzs8//wyTyYSoqCir56OioqDT6Zp9TUZGBjQajeXRrVs3KX25crX94zhH00fh0BIGHCIicpzIUKXUOk/hsSGnPebPnw+9Xm95nDt3Tkq7HQPbt4fU9yvHQhPcQUofiIiIWrJlxn1S6zyFx4aciIgI+Pv7o7y83Or58vJyaLXaZl8TGBgItVpt9ZBhx7Nt3wmc01NEROQs4SFKdAlpfZSmS4gS4beo8TQeG3KUSiXuvfde5ObmWp4zm83Izc1FYmKiU/vyq/AgKP0VNtX2Cg9gwCEiIqc7uGhki0GnS4gSBxeNdHKPHM+jVxjNmTMHU6dOxcCBAzFo0CD8/e9/x5UrV/D44487vS+nXxmDOxZmwWhqeWV60ZJkhKg8+pQTEZEHO7hoJCprjJi87mtUVBsRGarElhn3ed0IThOP/sadNGkSfvrpJ6Snp0On06Ffv37Izs6+aTGys5x+ZQzOV9Zh6KrdVs9vfGwQhsV3cUmfiIiIrhceosSuOf/l6m44hUII4V0XxbeBwWCARqOBXq+Xtj6HiIiIHMvW72+PXZNDRERE1BqGHCIiIvJKDDlERETklRhyiIiIyCsx5BAREZFXYsghIiIir8SQQ0RERF6JIYeIiIi8EkMOEREReSWP3tbBXk03ezYYDC7uCREREdmq6Xv7Vps2+HTIqa6uBgB069bNxT0hIiKitqquroZGo2nxuE/vXWU2m3HhwgWEhoZCoVBIa9dgMKBbt244d+4c98SShOdULp5PuXg+5eM5lcvbzqcQAtXV1YiJiYGfX8srb3x6JMfPzw9du3Z1WPtqtdor/mdyJzyncvF8ysXzKR/PqVzedD5bG8FpwoXHRERE5JUYcoiIiMgrMeQ4QGBgIBYvXozAwEBXd8Vr8JzKxfMpF8+nfDyncvnq+fTphcdERETkvTiSQ0RERF6JIYeIiIi8EkMOEREReSWGHCIiIvJKDDkO8PbbbyM2NhYqlQqDBw9GQUGBq7vkchkZGfj1r3+N0NBQREZGYvz48Th16pRVTX19PdLS0tC5c2eEhIRg4sSJKC8vt6opKyvD2LFjERwcjMjISLz44otobGy0qvnyyy8xYMAABAYGolevXtiwYYOjP57LrVy5EgqFArNnz7Y8x/PZdufPn8ejjz6Kzp07IygoCH379sWhQ4csx4UQSE9PR3R0NIKCgpCUlIQzZ85YtVFZWYnU1FSo1WqEhYVh2rRpqKmpsao5duwYhg8fDpVKhW7dumHVqlVO+XzOZDKZ8PLLLyMuLg5BQUHo2bMn/vKXv1jtNcTz2bq9e/di3LhxiImJgUKhwNatW62OO/P8ffLJJ+jduzdUKhX69u2LrKws6Z/XIQRJtWXLFqFUKsU//vEPceLECTF9+nQRFhYmysvLXd01l0pOThbvv/++KCoqEkeOHBFjxowR3bt3FzU1NZaap59+WnTr1k3k5uaKQ4cOiSFDhoj77rvPcryxsVEkJCSIpKQk8c0334isrCwREREh5s+fb6n57rvvRHBwsJgzZ44oLi4Wb775pvD39xfZ2dlO/bzOVFBQIGJjY8Xdd98tnnvuOcvzPJ9tU1lZKXr06CH++Mc/ivz8fPHdd9+JnTt3irNnz1pqVq5cKTQajdi6das4evSo+M1vfiPi4uJEXV2dpSYlJUXcc8894sCBA2Lfvn2iV69e4pFHHrEc1+v1IioqSqSmpoqioiLx4YcfiqCgIPHuu+869fM62iuvvCI6d+4stm/fLkpLS8Unn3wiQkJCxBtvvGGp4flsXVZWlli4cKH49NNPBQDx2WefWR131vnbv3+/8Pf3F6tWrRLFxcVi0aJFokOHDuL48eMOPwf2YsiRbNCgQSItLc3yb5PJJGJiYkRGRoYLe+V+KioqBACxZ88eIYQQVVVVokOHDuKTTz6x1JSUlAgAIi8vTwhx7Qfez89P6HQ6S82aNWuEWq0WV69eFUII8dJLL4m77rrL6r0mTZokkpOTHf2RXKK6ulrcfvvtIicnR9x///2WkMPz2XZz584Vw4YNa/G42WwWWq1WvPbaa5bnqqqqRGBgoPjwww+FEEIUFxcLAOLgwYOWmh07dgiFQiHOnz8vhBDinXfeEZ06dbKc46b3vvPOO2V/JJcaO3aseOKJJ6yemzBhgkhNTRVC8Hy21Y0hx5nn7/e//70YO3asVX8GDx4snnrqKamf0RE4XSWR0WhEYWEhkpKSLM/5+fkhKSkJeXl5LuyZ+9Hr9QCA8PBwAEBhYSEaGhqszl3v3r3RvXt3y7nLy8tD3759ERUVZalJTk6GwWDAiRMnLDXXt9FU463nPy0tDWPHjr3pM/N8tt3nn3+OgQMH4ne/+x0iIyPRv39/vPfee5bjpaWl0Ol0VudDo9Fg8ODBVuc0LCwMAwcOtNQkJSXBz88P+fn5lpoRI0ZAqVRaapKTk3Hq1ClcvnzZ0R/Tae677z7k5ubi9OnTAICjR4/iq6++wujRowHwfNrLmefPk38PMORI9PPPP8NkMll9aQBAVFQUdDqdi3rlfsxmM2bPno2hQ4ciISEBAKDT6aBUKhEWFmZVe/250+l0zZ7bpmOt1RgMBtTV1Tni47jMli1bcPjwYWRkZNx0jOez7b777jusWbMGt99+O3bu3ImZM2fi2WefxQcffADgl3PS2s+3TqdDZGSk1fGAgACEh4e36bx7g3nz5mHy5Mno3bs3OnTogP79+2P27NlITU0FwPNpL2eev5ZqPOH8+vQu5OQaaWlpKCoqwldffeXqrnisc+fO4bnnnkNOTg5UKpWru+MVzGYzBg4ciBUrVgAA+vfvj6KiIqxduxZTp051ce88z8cff4xNmzZh8+bNuOuuu3DkyBHMnj0bMTExPJ/kNBzJkSgiIgL+/v43XcFSXl4OrVbrol65l1mzZmH79u344osv0LVrV8vzWq0WRqMRVVVVVvXXnzutVtvsuW061lqNWq1GUFCQ7I/jMoWFhaioqMCAAQMQEBCAgIAA7NmzB6tXr0ZAQACioqJ4PtsoOjoa8fHxVs/16dMHZWVlAH45J639fGu1WlRUVFgdb2xsRGVlZZvOuzd48cUXLaM5ffv2xZQpU/D8889bRh55Pu3jzPPXUo0nnF+GHImUSiXuvfde5ObmWp4zm83Izc1FYmKiC3vmekIIzJo1C5999hl2796NuLg4q+P33nsvOnToYHXuTp06hbKyMsu5S0xMxPHjx61+aHNycqBWqy1fTomJiVZtNNV42/l/8MEHcfz4cRw5csTyGDhwIFJTUy3/zfPZNkOHDr3ptganT59Gjx49AABxcXHQarVW58NgMCA/P9/qnFZVVaGwsNBSs3v3bpjNZgwePNhSs3fvXjQ0NFhqcnJycOedd6JTp04O+3zOVltbCz8/668Yf39/mM1mADyf9nLm+fPo3wOuXvnsbbZs2SICAwPFhg0bRHFxsZgxY4YICwuzuoLFF82cOVNoNBrx5ZdfiosXL1oetbW1lpqnn35adO/eXezevVscOnRIJCYmisTERMvxpkueR40aJY4cOSKys7NFly5dmr3k+cUXXxQlJSXi7bff9tpLnm90/dVVQvB8tlVBQYEICAgQr7zyijhz5ozYtGmTCA4OFhs3brTUrFy5UoSFhYl//etf4tixY+K///u/m71kt3///iI/P1989dVX4vbbb7e6ZLeqqkpERUWJKVOmiKKiIrFlyxYRHBzsFZc8X2/q1KniV7/6leUS8k8//VRERESIl156yVLD89m66upq8c0334hvvvlGABB/+9vfxDfffCN++OEHIYTzzt/+/ftFQECA+J//+R9RUlIiFi9ezEvIfdmbb74punfvLpRKpRg0aJA4cOCAq7vkcgCafbz//vuWmrq6OvHMM8+ITp06ieDgYPHwww+LixcvWrXz/fffi9GjR4ugoCAREREhXnjhBdHQ0GBV88UXX4h+/foJpVIpbrvtNqv38GY3hhyez7bbtm2bSEhIEIGBgaJ3795i3bp1VsfNZrN4+eWXRVRUlAgMDBQPPvigOHXqlFXNpUuXxCOPPCJCQkKEWq0Wjz/+uKiurraqOXr0qBg2bJgIDAwUv/rVr8TKlSsd/tmczWAwiOeee050795dqFQqcdttt4mFCxdaXarM89m6L774otnfm1OnThVCOPf8ffzxx+KOO+4QSqVS3HXXXSIzM9Nhn1smhRDX3X6SiIiIyEtwTQ4RERF5JYYcIiIi8koMOUREROSVGHKIiIjIKzHkEBERkVdiyCEiIiKvxJBDREREXokhh4iIiLwSQw4RERF5JYYcIiIi8koMOUREROSVGHKIiIjIK/1/3MB2eG3bJncAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter([v for v in range(len(parentVTDno))],parentVTDno)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "55d64c64-b473-49d0-b863-d4123cbb9b6c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "confirming vtd 0 is not in the map but missing from the parent vtd list\n",
      "confirming vtd 2000 is not in the map but missing from the parent vtd list\n",
      "confirming vtd 4000 is not in the map but missing from the parent vtd list\n",
      "confirming vtd 6000 is not in the map but missing from the parent vtd list\n",
      "confirming vtd 8000 is not in the map but missing from the parent vtd list\n",
      "confirming vtd 10000 is not in the map but missing from the parent vtd list\n"
     ]
    }
   ],
   "source": [
    "for v in range(nVTDs):\n",
    "    if v %2000 == 0:\n",
    "        print(\"confirming vtd\",v,\"is not in the map but missing from the parent vtd list\")\n",
    "    if MAP.contains(vtdGeom[v].centroid) and v not in parentVTDno:\n",
    "        print(\"Uhoh,\",v,\"is in the map but not in the parent vtd list\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "ecd50c96-51ce-4d83-b0df-e8c645c35815",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after above patching, write these contiguous lists to a file, converting to vtd lists\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 if there were NO fragmented VTDs 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on full or partial VTD master list for unit 0\n",
      "working on full or partial VTD master list for unit 2000\n",
      "working on full or partial VTD master list for unit 4000\n",
      "working on full or partial VTD master list for unit 6000\n",
      "working on full or partial VTD master list for unit 8000\n",
      "Now converting unit lists to vtd lists for all HDs\n"
     ]
    }
   ],
   "source": [
    "#THIS WORKS FOR BOTH VTD- AND UNIT-BASED (FRAG VTD) -- **NOTE: DOES NOT ADD IN CUT DISTRICTS AND REBALANCE WEIGHTS\n",
    "print(\"after above patching, write these contiguous lists to a file, converting to vtd lists\")\n",
    "noFrag = int(input(\"enter 1 if there were NO fragmented VTDs\"))  #for simple states where units are at least whole vtd's\n",
    "tList = [t for t in range(nHDs)]\n",
    "vtdList = [list() for t in range(nHDs)]\n",
    "unitVTDlist, unitFragVTDlist, unitVTDfrac = [list() for u in range(nUnits)], [list() for u in range(nUnits)], [list() for u in range(nUnits)]\n",
    "unitFullVTDlist, unitPartialVTDlist =       [list() for u in range(nUnits)], [list() for u in range(nUnits)]\n",
    "\n",
    "for u in range(nUnits):\n",
    "    if u %2000 == 0:\n",
    "        print(\"working on full or partial VTD master list for unit\",u)\n",
    "    if allUnits[u] % 1 == 0.5 :\n",
    "        c = int(allUnits[u])\n",
    "        unitVTDlist[u] = countyTractList[c].copy()\n",
    "        unitFullVTDlist[u] = countyTractList[c].copy()\n",
    "    if allUnits[u] % 1 == 0.25 :\n",
    "        CCBnumber = int(allUnits[u])\n",
    "        for c in CCBlist[CCBnumber] :\n",
    "            unitVTDlist[u] += countyTractList[c]\n",
    "            unitFullVTDlist[u] += countyTractList[c]\n",
    "    if allUnits[u] % 1 == 0:\n",
    "        if noFrag == 1:\n",
    "            unitVTDlist[u].append(allUnits[u] )\n",
    "            for i,vv in enumerate(surrounders):\n",
    "                if allUnits[u] == vv:\n",
    "                    unitVTDlist[u].append(surroundedVTDs[i])\n",
    "        else:\n",
    "            unitFragVTDlist[u].append(allUnits[u])\n",
    "            for i,vv in enumerate(surrounders):\n",
    "                if allUnits[u] == vv:\n",
    "                    unitFragVTDlist[u].append(surroundedVTDs[i])\n",
    "            vtdFrac = [0. for V in range(nVTDs)]\n",
    "            for vv in unitFragVTDlist[u]:\n",
    "                V = parentVTDno[vv]\n",
    "                if len(VTDchildren[V]) == 1:  #nonfragmented vtd\n",
    "                    vtdFrac[V] = 1.\n",
    "                else:\n",
    "                    if tractPop[V] > 0:\n",
    "                        vtdFrac[V] += fragVTDgeom[vv].area / vtdGeom[V].area #fragVTDpop[uu] / tractPop[v]  #we overwrote the frag pops earlier; can't use\n",
    "            for v in range(nVTDs):\n",
    "                if vtdFrac[v] > 0.0001:\n",
    "                    if vtdFrac[v] > 0.999:\n",
    "                        unitFullVTDlist[u].append(v)\n",
    "                    else:\n",
    "                        unitPartialVTDlist[u].append(v)\n",
    "                        unitVTDfrac[u].append(vtdFrac[v] )\n",
    "                                    \n",
    "HDpartialVTDlist, HDfullVTDlist, HDvtdFrac = [list() for t in range(nHDs)] ,[list() for t in range(nHDs)],[list() for t in range(nHDs)]               \n",
    "print(\"Now converting unit lists to vtd lists for all HDs\")\n",
    "if noFrag == 1:\n",
    "    for t in popHDlist:\n",
    "        for u in HDunitList[t]:\n",
    "            vtdList[t] += unitVTDlist[u]\n",
    "    outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":vtdList,\"partials\":HDpartialVTDlist,\n",
    "                           \"HDvtdFrac\":HDvtdFrac,\"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "else:\n",
    "    for t in popHDlist:\n",
    "        partialList, partialFrac = list(), list()  #for many HDs, we'll recover whole VTDs when aggregating units\n",
    "        for u in HDunitList[t]:\n",
    "            HDfullVTDlist[t] +=   unitFullVTDlist[u] \n",
    "            partialList +=         unitPartialVTDlist[u]\n",
    "            partialFrac +=          unitVTDfrac[u]\n",
    "        partialSet = set(partialList)  #non-duplicated set of partials across the HD, prepping to aggregate where possible\n",
    "        partialSetFrac, partialSetList = [0. for v in partialSet], list(partialSet)\n",
    "        for i,v in enumerate(partialList):\n",
    "            partialSetFrac[partialSetList.index(v)] += partialFrac[i]\n",
    "        for i,v in enumerate(partialSetList):\n",
    "            if partialSetFrac[i] > 0.999:  #the district has all the fragments of the original VTD contained in the HD's units\n",
    "                HDfullVTDlist[t].append(v)\n",
    "            else:\n",
    "                HDpartialVTDlist[t].append(v)\n",
    "                HDvtdFrac[t].append(      r5(partialSetFrac[i]) )  #save the aggregated fraction of this VTD across all units\n",
    "    outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":HDfullVTDlist,\"partials\":HDpartialVTDlist,\n",
    "                           \"HDvtdFrac\":HDvtdFrac,\"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"patchedVTDs.csv\"   #patchDown, PatchUp, PatchBoth\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "5075814f-4a75-4807-ad8d-b3cc969cb470",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10084 10084 10084 10084 10084 10084\n"
     ]
    }
   ],
   "source": [
    "\n",
    "HDweight = HDweight[0:nHDs]\n",
    "HDvPop = HDvPop[0:nHDs]\n",
    "HDweight = HDweight[0:nHDs]\n",
    "HDfullVTDlist = HDfullVTDlist[0:nHDs]\n",
    "HDpartialVTDlist = HDpartialVTDlist[0:nHDs]\n",
    "HDvtdFrac = HDvtdFrac[0:nHDs]\n",
    "hdCPx, hdCPy = hdCPx[0:nHDs], hdCPy[0:nHDs]\n",
    "print(nHDs,len(tList), len(HDweight), len(HDvPop), len(HDvtdFrac), len(hdCPx) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "e385f357-5b7e-46f5-b054-c5c38d799395",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.0 10084\n"
     ]
    }
   ],
   "source": [
    "print(np.sum(HDweight), nHDs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "8d922813-2854-41d7-9405-22db5d5d5a59",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now append the cut districts and adjust the HDweights\n",
      "17 0 are the number of HD-drawn and cut districts\n"
     ]
    }
   ],
   "source": [
    "print(\"Now append the cut districts and adjust the HDweights\")\n",
    "print(nDistricts,nCutDistricts,\"are the number of HD-drawn and cut districts\")\n",
    "HDweight = [nDistricts/float(nCutDistricts + nDistricts) * HDweight[t] for t in range(nHDs)]\n",
    "tList = [t for t in range(nHDs)]\n",
    "if type(hdCPx) != type(list()):\n",
    "    hdCPx, hdCPy = hdCPx.to_list(), hdCPy.to_list()\n",
    "for L in allCutLists:\n",
    "    tList.append(len(tList))\n",
    "    HDweight.append(1./(nCutDistricts + nDistricts))\n",
    "    pop = np.sum([tractPop[v] for v in L])\n",
    "    HDvPop.append(pop )\n",
    "    HDfullVTDlist.append(L)\n",
    "    HDpartialVTDlist.append(list() )\n",
    "    HDvtdFrac.append(list() )\n",
    "    hdCPx.append(np.sum([tractPop[v]*tractCPx[v] for v in L]) / pop )\n",
    "    hdCPy.append(np.sum([tractPop[v]*tractCPy[v] for v in L]) / pop )\n",
    "    \n",
    "\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":HDfullVTDlist,\"partials\":HDpartialVTDlist,\n",
    "                        \"HDvtdFrac\":HDvtdFrac,\"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"patchedVTDs.csv\"   #patchDown, PatchUp, PatchBoth #patchedWithCutsVTDs\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "b0b611f7-6c35-495d-b38c-c848317d63ab",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.0\n"
     ]
    }
   ],
   "source": [
    "print(np.sum(HDweight))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "b9d808de-119f-4197-8e0c-8407c105d789",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking that VTDs are represented 1.0 across all units\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"checking that VTDs are represented 1.0 across all units\")\n",
    "vtdUSE = [0. for v in range(nVTDs)]\n",
    "for u in range(nUnits):\n",
    "    for v in unitFullVTDlist[u]:\n",
    "        vtdUSE[v] += 1\n",
    "    for i,v in enumerate(unitPartialVTDlist[u]):\n",
    "        vtdUSE[v] += unitVTDfrac[u][i]\n",
    "plotVTDs, plotUses = list(), list()\n",
    "for v in range(nVTDs):\n",
    "    if tractPop[v] > 0  and v not in allCutVTDs:\n",
    "        plotVTDs.append(v)\n",
    "        plotUses.append(vtdUSE[v])\n",
    "plt.scatter(plotVTDs, plotUses)\n",
    "plt.show()\n",
    "for i,v in enumerate(plotVTDs):\n",
    "    if plotUses[i] > 0.1 and plotUses[i] < 0.9 :\n",
    "        print(v,tractPop[v], plotUses[i],\"vtd no, its pop, and usage across all units\")\n",
    "        plotPoly(tractGeom[v])\n",
    "unused = list()\n",
    "for v in range(nVTDs):\n",
    "    if vtdUSE[v] < 0.2 and MAP.contains(vtdGeom[v].centroid) and tractPop[v] > 0:\n",
    "        unused.append(v)\n",
    "        #print(v,\"in county\",countyNo[v],\"has pop\",tractPop[v],\"and map-total usage of\",vtdUSE[v],\"its surroundedness is\",v in surroundedVTDs)\n",
    "        plotPoly(vtdGeom[v].centroid.buffer(0.1))\n",
    "        plotCenter(v,vtdGeom[v],8)\n",
    "    #if vtdUSE[v] > 0.2 and vtdUSE[v] < 0.95:\n",
    "    #    plotCenter(r3(vtdUSE[v]),vtdGeom[v])\n",
    "plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "3d2a393c-5ab8-4140-80eb-1153c2ef41f9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for u in range(nUnits):\n",
    "    if unitUse[u]  < 0.9:\n",
    "        plotPoly(unitGeom[u],0.2)\n",
    "        plotCenter(r3(unitUse[u]),unitGeom[u],6)\n",
    "    if  unitUse[u]  > 1.1:\n",
    "        plotPoly(unitGeom[u],1.2)\n",
    "        plotCenter(r3(unitUse[u]),unitGeom[u],6)\n",
    "plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "404935e6-f0de-4b51-9db9-020aa208f852",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "integrity check: vtd-based pops.  These should all be within single digits\n",
      "x = n surrounded, y= unit - vtd-based\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"integrity check: vtd-based pops.  These should all be within single digits\")\n",
    "HDvtdbasedPop = [0. for t in range(nHDs)]\n",
    "HDvPop = [0. for t in range(nHDs)]\n",
    "nSurrs = [0. for t in range(nHDs)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "        if u in surroundedVTDs:\n",
    "            nSurrs[t] += 1\n",
    "    for v in HDfullVTDlist[t]:\n",
    "        HDvtdbasedPop[t] += origVTDpop[v] #tractPop[v]\n",
    "    for i,v in enumerate(HDpartialVTDlist[t]):\n",
    "        HDvtdbasedPop[t] += HDvtdFrac[t][i] * origVTDpop[v] #tractPop[v] also works\n",
    "        \n",
    "plt.scatter([nSurrs[t] for t in popHDlist], [HDvPop[t] - HDvtdbasedPop[t] for t in popHDlist] )\n",
    "print(\"x = n surrounded, y= unit - vtd-based\")\n",
    "plt.show()\n",
    "plotThis = False\n",
    "for t in popHDlist:  #seems like for TN, we lost a vtd in converting from unit-based to vtd-based\n",
    "    if abs(HDvPop[t] - HDvtdbasedPop[t]) > 10:\n",
    "        plotThis = True\n",
    "        print(\"t, HDunit-based pop - pop from vtd-based HDs\",t,r3(HDvPop[t] - HDvtdbasedPop[t]) )\n",
    "        plotPoly(tractCP[t].buffer(0.1))\n",
    "if plotThis:\n",
    "    plotPoly(MAP)\n",
    "    print(\"Here are the HD centers with significant pop difference between unit-based and vtd-based HD lists\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef27af54-daf5-4e8f-9230-bce5b0b1e705",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "id": "3ad3342b-b8e3-46f5-a3e5-f49df386b88f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, read in the votes by vtd to compute ensemble vote margin vs. true state vote margin\n",
      "Let's read in the 2020 and 2016 voting data for IL\n",
      "In year/election 2020 Dem and GOP total votes were 3471912 2446894 for a stateGOP of 0.41341\n",
      "There are a total of 10084  vote-mapped voting districts from election(s) in year  2020\n",
      "In year/election 2016 Dem and GOP total votes were 3090729 2146016 for a stateGOP of 0.4098\n",
      "There are a total of 10084  vote-mapped voting districts from election(s) in year  2016\n"
     ]
    }
   ],
   "source": [
    "print(\"Now, read in the votes by vtd to compute ensemble vote margin vs. true state vote margin\")\n",
    "#note: we started w possibility of separate election --> 2020 vtd files by year.  Now we use ALARM combined 2016+2020 --> 2020 csv's for all exc CA\n",
    "# copied from \"HDpartisanAnalysis\"\n",
    "print(\"Let's read in the 2020 and 2016 voting data for\",STATE)\n",
    "#DemCandidates, RepCandidates, vestDFs = [\"G16PREDCLI\"], [\"G16PRERTRU\" ], list()\n",
    "#DemCandidates, RepCandidates, vestDFs = [\"G20PREDBID\", \"G16PREDCli\"], [\"G20PRERTRU\" ,\"G16PRERTru\" ], list()\n",
    "DemCandidates, RepCandidates, vestDFs = [\"pre_20_dem_bid\", \"pre_16_dem_cli\"], [\"pre_20_rep_tru\" ,\"pre_16_rep_tru\" ], list()\n",
    "nYears = 2\n",
    "unitIDs, vestReps,vestDems,yearLean = [list()]*nYears, [0]*nYears, [0]*nYears, [0.5]*nYears\n",
    "years = [str(2020),str(2016)]\n",
    "DemVotes, RepVotes = [list() for y in years], [list() for y in years]\n",
    "vestDir = \"./state_map_files/\" + STATE.lower()\n",
    "vestDF = pd.read_csv(vestDir + \"_2020_vtd.csv\")\n",
    "mergedDF = vestDF.copy() #pd.merge(mergedDF,vestDF, on = \"GEOID20\")\n",
    "for y,year in enumerate(years):\n",
    "    DemVotes[y], RepVotes[y], unitIDs[y] = mergedDF[DemCandidates[y]], mergedDF[RepCandidates[y]], vestDF[(\"GEOID20\")]\n",
    "    vestDems[y], vestReps[y] = np.sum(DemVotes[y]), np.sum(RepVotes[y])\n",
    "    yearLean[y] = vestReps[y]/float(vestDems[y]+vestReps[y])\n",
    "    print(\"In year/election\",year,\"Dem and GOP total votes were\",int(vestDems[y]),int(vestReps[y]),\"for a stateGOP of\",r5(yearLean[y]) )\n",
    "    nVTDs = len(DemVotes[y])\n",
    "    print(\"There are a total of\",nVTDs,\" vote-mapped voting districts from election(s) in year \",years[y])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f628069d-4177-401e-bf49-b7f194d0ef8b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "5cf73783-4a48-4a3f-a2e3-c1b9ff32c859",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now let's read in our ensemble of HD districts for IL\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the filename with the vtd assignments to districts; e.g. NC2666patchedWithCutsVTDs.csv IL10084patchedVTDs.csv\n",
      "enter the number of Congr'l districts in the state; e.g. 8 17\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This ensemble or enacted map describes 10084 drawn districts.  This state has 17 districts per map\n",
      "converting vtd list strings to vtd lists by drawn district ...\n",
      "the total weight across all rows should be 1.000, actually is 1.0\n",
      "I am assuming we already read in a 'tractPopFile' of Census vtd geoms & pops with a GEOID20 column\n",
      "translating from HD order of precinct rows to VEST order\n"
     ]
    }
   ],
   "source": [
    "print(\"Now let's read in our ensemble of HD districts for\",STATE)\n",
    "infilename = input(\"enter the filename with the vtd assignments to districts; e.g. NC2666patchedWithCutsVTDs.csv\")\n",
    "\n",
    "HDdf = pd.read_csv(\"2024state_HD_output/\"+infilename)\n",
    "nRows = len(HDdf)\n",
    "nStateDistricts = int(input(\"enter the number of Congr'l districts in the state; e.g. 8\"))\n",
    "print(\"This ensemble or enacted map describes\",nRows,\"drawn districts.  This state has\",nStateDistricts,\"districts per map\")\n",
    "\n",
    "HDvPop = HDdf[\"HDvPop\"].to_list()\n",
    "HDweight = HDdf['HDweight'].to_list()\n",
    "#tractPop = HDdf['tractPop'].to_list()\n",
    "#statePop = np.sum(tractPop)\n",
    "tractCPx = HDdf['centroid x'].to_list()\n",
    "tractCPy = HDdf['centroid y'].to_list()\n",
    "HDvtdListString = HDdf[\"HDvtdList\"]\n",
    "print(\"converting vtd list strings to vtd lists by drawn district ...\")\n",
    "HDvtdList = [list() for t in range(nRows) ]\n",
    "for t in range(nRows):\n",
    "    if HDvtdListString[t] != \"[]\":\n",
    "        HDvtdList[t] = ast.literal_eval(HDvtdListString[t])\n",
    "\n",
    "if \"partials\" in HDdf.columns.values: #\"splitTractNo\" #.to_list():\n",
    "    splitTractList, splitTractUseList = HDdf['partials'], HDdf['HDvtdFrac']\n",
    "    splitTractNo = [ast.literal_eval(splitTractList[t])    for t in range(nRows)]\n",
    "    splitTractUse = [ast.literal_eval(splitTractUseList[t]) for t in range(nRows)]\n",
    "else :  #incoming file didn't use any partial units, only whole ones\n",
    "    splitTractNo, splitTractUse = [[] for t in range(nRows)] , [ [] for t in range(nRows)]\n",
    "\n",
    "print(\"the total weight across all rows should be 1.000, actually is\",r5(np.sum(HDweight)) )\n",
    "print(\"I am assuming we already read in a 'tractPopFile' of Census vtd geoms & pops with a GEOID20 column\")\n",
    "censusGEOID20 = [ str( tractPopFile['GEOID20'][i]) for i in range(len(tractPopFile['GEOID20'])) ] #force strings to match\n",
    "miniHDdf = pd.DataFrame( {\"GEOID20\":censusGEOID20} )\n",
    "vestNo = [v for v in range(nVTDs)]\n",
    "print(\"translating from HD order of precinct rows to VEST order\")\n",
    "mergedGEO = [str(mergedDF['GEOID20'][i]) for i in range(len(mergedDF['GEOID20'])) ]  #force strings to match\n",
    "miniVestDF = pd.DataFrame( {\"GEOID20\":mergedGEO, \"vestNo\":vestNo} )\n",
    "mappingDF = pd.merge(miniHDdf,miniVestDF,on=\"GEOID20\")\n",
    "vestID = mappingDF['vestNo']  #this maps each named unit in a HDVL to the correct vestNo row with voting data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "540c6d1d-7728-48bf-90f0-f124b25ac7c2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sanity check - Dem-leaning vtds for year 2020\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"sanity check - Dem-leaning vtds for year\",years[0])  #for MA, do GOP-leaning.  Other states, use Dem-leaning\n",
    "for v in range(nVTDs):\n",
    "    plotPoly(vtdGeom[v],0.2)\n",
    "    if DemVotes[0][vestID[v]] > RepVotes[0][vestID[v]]:\n",
    "        plt.text(vtdGeom[v].centroid.x, vtdGeom[v].centroid.y, \"D\", color = \"blue\",fontsize=6)\n",
    "        #plotCenter(\"d\",vtdGeom[v],6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "56ed7e9d-1400-4848-892e-737555552d58",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's compute the ensemble average vote margin (GOP -  Dem total votes) for 2020 vs. true statewide result\n",
      "working on drawn district no 0\n",
      "working on drawn district no 1000\n",
      "working on drawn district no 2000\n",
      "working on drawn district no 3000\n",
      "working on drawn district no 4000\n",
      "working on drawn district no 5000\n",
      "working on drawn district no 6000\n",
      "working on drawn district no 7000\n",
      "working on drawn district no 8000\n",
      "working on drawn district no 9000\n",
      "working on drawn district no 10000\n",
      "here is the table of Dem and Rep votes, vote margin for true 2020 vs. ensemble\n",
      "true 2020: 3471912 2446894 -1025017\n",
      "ensemble : 3468919 2463284 -1005635\n",
      "the true and ensemble state GOP leans are 0.41341 0.4152393530331593\n"
     ]
    }
   ],
   "source": [
    "print(\"Now, let's compute the ensemble average vote margin (GOP -  Dem total votes) for 2020 vs. true statewide result\")\n",
    "nDrawnDistricts = len(HDweight)  #now including cut districts\n",
    "nMapDistricts = nCutDistricts + nDistricts\n",
    "nEnsembleDems, nEnsembleReps = [0.]*nYears, [0.]*nYears\n",
    "y=0\n",
    "for t in range(nDrawnDistricts):\n",
    "    if t%1000 == 0:\n",
    "        print(\"working on drawn district no\",t)\n",
    "    nEnsembleDems[y] += nMapDistricts* HDweight[t] * ( np.sum([DemVotes[y][vestID[v]] for v in HDvtdList[t] ])\n",
    "                                               + np.sum([DemVotes[y][vestID[v]] * splitTractUse[t][i] for i,v in enumerate(splitTractNo[t]) ])  )\n",
    "    nEnsembleReps[y] += nMapDistricts* HDweight[t] * ( np.sum([RepVotes[y][vestID[v]] for v in HDvtdList[t] ])\n",
    "                                               + np.sum([RepVotes[y][vestID[v]] * splitTractUse[t][i] for i,v in enumerate(splitTractNo[t]) ])  )\n",
    "\n",
    "print(\"here is the table of Dem and Rep votes, vote margin for true 2020 vs. ensemble\")\n",
    "print(\"true 2020:\",int(vestDems[y]),int(vestReps[y]),              int(vestReps[y] - vestDems[y]) )\n",
    "print(\"ensemble :\",int(nEnsembleDems[y]),int(nEnsembleReps[y]),    int(nEnsembleReps[y] - nEnsembleDems[y]) )\n",
    "print(\"the true and ensemble state GOP leans are\",r5(vestReps[y]/(vestReps[y]+vestDems[y])),\n",
    "      nEnsembleReps[y]/(nEnsembleReps[y]+nEnsembleDems[y]) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "5c607c63-df0d-4334-8131-368c090c76d2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total drawn districts, HD-drawn, map districts 10084 10084 17\n"
     ]
    }
   ],
   "source": [
    "print(\"total drawn districts, HD-drawn, map districts\",nDrawnDistricts,nHDs, nMapDistricts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bb0d0d12-6bf4-4d5f-9236-fa8735393e98",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
